AUTHOR=Wei Yiping , Shi Meng , Nie Yong , Wang Cui , Sun Fei , Jiang Wenting , Hu Wenjie , Wu Xiaolei 

TITLE=Integrated analysis of the salivary microbiome and metabolome in chronic and aggressive periodontitis: A pilot study

JOURNAL=Frontiers in Microbiology

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/microbiology/articles/10.3389/fmicb.2022.959416

DOI=10.3389/fmicb.2022.959416

ISSN=1664-302X

ABSTRACT=This pilot study was designed to identify the salivary microbial community and metabolic profiles in patients with generalized periodontitis using 16S rRNA gene high-throughput sequencing and gas chromatography-mass spectrometry. A total of 36 saliva samples were collected from 13 patients with aggressive periodontitis (AgP), 13 patients with chronic periodontitis (ChP) and 10 subjects with periodontal health (PH). Our results revealed that the salivary microbial community and metabolites composition differed significantly between patients with periodontitis and healthy controls. Striking differences were found in the composition of salivary metabolites between AgP and ChP. The genus Treponema, Peptococcus, Catonella, Desulfobulbus, Peptostreptococcaceae_[XI] [G-2], [G-3] [G-4], [G-6] and [G-9], Bacteroidetes_[G-5], TM7_[G-5], Dialister, Eikenella, Fretibacterium and Filifactor were present higher levels in patients with periodontitis than in healthy participants. The biochemical pathways that significantly different between ChP and AgP included pyrimidine metabolism, beta-alanine metabolism, alanine, aspartate and glutamate metabolism, citrate cycle and arginine and proline metabolism. The differential metabolites between ChP and AgP groups such as urea, beta alanine, 3-aminoisobutyric acid and thymine had the most significant correlations with genera. These differential metabolites and microorganisms may be used as potential biomarkers to monitor occurrence and development of periodontitis through the utilization of noninvasive and convenient saliva samples. Integration of microbial data and metabolomic data may help us understand the potential mechanism of periodontitis and offer potential biomarkers.