The salivary microbiota (SM), comprising bacteria shed from oral surfaces, has been shown to be individualized, temporally stable and influenced by diet and lifestyle. SM reflects local bacterial alterations of the supragingival and subgingival microbiota, and periodontitis and dental-caries associated characteristics of SM have been reported. Also, data suggest an impact of systemic diseases on SM as demonstrated in patients with a wide variety of systemic diseases including diabetes, cancer, HIV and rheumatoid arthritis. The presence of systemic diseases seems to influence salivary levels of specific bacterial species, as well as α- and β-diversity of SM. The composition of SM might thereby potentially mirror oral and general health status. The contentious development of advanced molecular techniques such as metagenomics, metatranscriptomics and metabolomics has enabled the possibility to address bacterial functions rather than presence in microbial samples. However, at present only a few studies have employed such techniques on SM to reveal functional and metabolic characteristics in oral health and disease. Future studies are therefore warranted to illuminate the possible impact of metabolic functions of SM on oral and general health status. Ultimately, such an approach has the possibility to reveal novel and personalized therapeutic avenues in oral and general medicine.

Bacterial profiles of saliva in relation to diet, lifestyle factors, and socioeconomic status

Saliva is a biological fluid suitable for biomarker analysis, and differences in the salivary microbiota in oral health and disease have been reported. For such comparative analyses, time of sampling is critical since the bacterial composition may vary throughout the day, i.e., diurnal variation. The purpose of this study is to compare the salivary microbiome over time to determine the optimal time for sampling. Stimulated saliva samples were collected from 5 orally healthy individuals in 4 h intervals for 24 h, and collection was repeated 7 days later (number of samples per person, n = 12, total number of samples, n = 60). Salivary microbiota was analyzed using the Human Oral Microbe Identification using Next Generation Sequencing (HOMINGS), and statistical analysis was performed using the Kruskal-Wallis test with Benjamini-Hochberg’s correction for multiple comparisons, cluster analysis, principal component analysis and correspondence analysis. From a total of 60 saliva samples, 477 probe targets were collectively identified with a mean number of probes per sample of 207 (range: 153–307). Little or no variation in microbial profiles within subjects was observed over time. Although there was considerable variation between subjects, microbial profiles within subjects were stable throughout a 24 hour period and after 1 week. Since there is little or no evidence of diurnal variation of the salivary microbiome, time of sampling of saliva is not critical for perturbation or other microbial studies.

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.

The purpose of this study was to compare microbial profiles of saliva, pooled and site-specific subgingival samples in patients with periodontitis. We tested the hypotheses that saliva can be an alternative to pooled subgingival samples, when screening for presence of periopathogens. Site specific subgingival plaque samples (n = 54), pooled subgingival plaque samples (n = 18) and stimulated saliva samples (n = 18) were collected from 18 patients with generalized chronic periodontitis. Subgingival and salivary microbiotas were characterized by means of HOMINGS (Human Oral Microbe Identification using Next Generation Sequencing) and microbial community profiles were compared using Spearman rank correlation coefficient. Pronounced intraindividual differences were recorded in site-specific microbial profiles, and site-specific information was in general not reflected by pooled subgingival samples. Presence of Porphyromonas gingivalis, Treponema denticola, Prevotella intermedia, Filifactor alocis, Tannerella forsythia and Parvimona micra in site-specific subgingival samples were detected in saliva with an AUC of 0.79 (sensitivity: 0.61, specificity: 0.94), compared to an AUC of 0.76 (sensitivity: 0.56, specificity: 0.94) in pooled subgingival samples. Site-specific presence of periodontal pathogens was detected with comparable accuracy in stimulated saliva samples and pooled subgingival plaque samples. Consequently, saliva may be a reasonable surrogate for pooled subgingival samples when screening for presence of periopathogens. Future large-scale studies are needed to confirm findings from this study.