Metagenomic and metatranscriptomic analysis of saliva reveals disease-associated microbiota in patients with periodontitis and dental caries

Abstract

The taxonomic composition of the salivary microbiota has been reported to differentiate between oral health and disease. However, information on bacterial activity and gene expression of the salivary microbiota is limited. The purpose of this study was to perform metagenomic and metatranscriptomic characterization of the salivary microbiota and test the hypothesis that salivary microbial presence and activity could be an indicator of the oral health status. Stimulated saliva samples were collected from 30 individuals (periodontitis: n = 10, dental caries: n = 10, oral health: n = 10). Salivary microbiota was characterized using metagenomics and metatranscriptomics in order to compare community composition and the gene expression between the three groups. Streptococcus was the predominant bacterial genus constituting approx. 25 and 50% of all DNA and RNA reads, respectively. A significant disease-associated higher relative abundance of traditional periodontal pathogens such as Porphyromonas gingivalis and Filifactor alocis and salivary microbial activity of F. alocis was associated with periodontitis. Significantly higher relative abundance of caries-associated bacteria such as Streptococcus mutans and Lactobacillus fermentum was identified in saliva from patients with dental caries. Multiple genes involved in carbohydrate metabolism were significantly more expressed in healthy controls compared to periodontitis patients. Using metagenomics and metatranscriptomics we show that relative abundance of specific oral bacterial species and bacterial gene expression in saliva associates with periodontitis and dental caries. Further longitudinal studies are warranted to evaluate if screening of salivary microbial activity of specific oral bacterial species and metabolic gene expression can identify periodontitis and dental caries at preclinical stages.

Fig. 1

Microbial diversity. a: Rarefaction curves expressed as number of reads assigned at species level (x-axis) and α-diversity (observed Species and Shannon index, y-axis) of salivary microbiota characterized using metagenomics and metatranscriptomics. b: Distribution of α-diversity among groups presented as boxplot (median, lower/upper quartile and standard deviation). c: β-diversity determined by Bray-Curtis dissimilarity and plotted using PCoA. Sample denotation: green: healthy controls, blue: dental caries, red: periodontitis

Fig. 2

Relative abundance. a: Top 20 predominant microbial genera. b: Top 20 predominant microbial species based on metagenomic and metatranscriptomic analyses

Fig. 3

Periodontitis and caries-associated salivary microbiota. a: Venn diagram displaying number and proportion of microbial species in salivary core and non-core microbiome based on metagenomic approach. b: Bacterial species with significantly higher relative abundance in oral health, dental caries or periodontitis. c: Venn diagram displaying number and proportion of microbial species in salivary core and non-core microbiome based on metatranscriptomic approach. d: Bacterial species with significantly higher relative abundance in oral health, dental caries or periodontitis. Sample denotation: green: healthy controls, blue: dental caries, red: periodontitis

Fig. 4

Salivary microbial activity. a: Log2 RNA/DNA ratio of the 13 bacterial phyla identified in saliva across all samples. b: Bacterial species identified with significantly different log2 RNA/DNA ratios in samples from patients with periodontitis (red), dental caries patients (blue) and orally healthy controls (green)

Fig. 5

Differentially expressed genes in the salivary metatranscriptome in dental health and disease. a: periodontitis patients (red) and healthy controls (green) and b: dental caries patients (blue) and healthy controls (green). Only significant differences as determined using DESeq2 negative binomial tests are shown (p < 0.05). KEGG orthologs (KO) numbers and Enzyme commission numbers are reported (EC) when applicable