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Introduction: Previous studies have largely explored the microbial composition and pathogenesis of pregnancy gingivitis. However, the patterns of microbial colonization during pregnancy in the absence of pregnancy gingivitis have rarely been studied. Characterization of the oral microbiome in pregnant women with healthy gingiva is an important initial step in understanding the role of the microbiome in progression to pregnancy gingivitis. Objectives: In this study, we compared the oral microbiome of pregnant women without gingivitis (healthy pregnancy) with pregnant women having gingivitis and nonpregnant healthy women to understand how pregnancy modifies the oral microbiome and induces progression to pregnancy gingivitis. Methods: Subgingival plaque samples were collected from Chinese pregnant women with gingivitis (n = 10), healthy pregnant women (n = 10), and nonpregnant healthy women (n = 10). The Illumina MiSeq platform was used to perform 16S rRNA gene sequencing targeting the V4 region. Results: The alpha and beta diversity was significantly different between pregnant and nonpregnant women, but minimal differences were observed between pregnant women with and without gingivitis. Interestingly, the oral bacterial community showed higher abundance of pathogenic taxa during healthy pregnancy as compared with nonpregnant women despite similar gingival and plaque index scores. However, when compared with overt pregnancy gingivitis, pathogenic taxa were less abundant during healthy pregnancy. PICRUSt analysis (phylogenetic investigation of communities by reconstruction of unobserved states) also suggested no difference in the functional capabilities of the microbiome during pregnancy, irrespective of gingival disease status. However, metabolic pathways related to amino acid metabolism were significantly increased in healthy pregnant women as compared with nonpregnant women. Conclusion: The presence of pathogenic taxa in healthy pregnancy and pre

Objectives: Large longitudinal cohort studies in infants are needed to understand oral microbiome maturation in relation to general health. The logistics of such studies are complex and costs involved high. Methods like home sampling by caretakers might be a solution to these issues. This study aimed to evaluate feasibility of home sampling by caretakers and to assess which oral niche provides the most reliable sample. Methods: In this cross-sectional study 30 mothers and their infants aged 2–15 months participated. Swabs of the tongue, buccal mucosa, saliva, and dental plaque of the mother and the infant were collected by the mother after watching an instruction video. Thereafter, the trained researcher repeated the sample collection. Variations on the sampling protocol were listed. Bacterial DNA was quantified and microbial composition was assessed using 16S rDNA amplicon sequencing. Results: None of the sampled niches appeared to be unfeasible based on interviews and observed variations on protocol. No significant differences in bacterial DNA concentration between operators (mother and researcher) were found. In infant's saliva, Shannon diversity of samples collected by the researcher was significantly higher than those collected by mothers (p = 0.0009) and the bacterial composition was influenced by variations on sampling protocol (p = 0.01). Conclusions: Home sampling by caretakers is a feasible method for oral sample collection in infants and mothers. Oral samples collected by mothers resemble samples collected by a trained researcher, with the tongue sample being the most similar and saliva the least. Clinical Significance: Home sampling can simplify longitudinal oral microbiota collection.

In the past decade, there has been a tremendous increase in studies on the link between oral microbiome and systemic diseases. However, variations in study design and confounding variables across studies often lead to inconsistent observations. In this narrative review, we have discussed the potential influence of study design and confounding variables on the current sequencing-based oral microbiome-systemic disease link studies. The current limitations of oral microbiome-systemic link studies on type 2 diabetes mellitus, rheumatoid arthritis, pregnancy, atherosclerosis, and pancreatic cancer are discussed in this review, followed by our perspective on how artificial intelligence (AI), particularly machine learning and deep learning approaches, can be employed for predicting systemic disease and host metadata from the oral microbiome. The application of AI for predicting systemic disease as well as host metadata requires the establishment of a global database repository with microbiome sequences and annotated host metadata. However, this task requires collective efforts from researchers working in the field of oral microbiome to establish more comprehensive datasets with appropriate host metadata. Development of AI-based models by incorporating consistent host metadata will allow prediction of systemic diseases with higher accuracies, bringing considerable clinical benefits.

Acylhomoserine lactones (AHLs), the quorum-sensing (QS) signals produced by a range of Gram-negative bacteria, are involved in biofilm formation in many pathogenic and environmental bacteria. Nevertheless, the current paradigm excludes a role of AHLs in dental plaque formation, while other QS signals, such as AI-2 and autoinducer peptides, have been demonstrated to play an important role in biofilm formation and virulence-related gene expression in oral pathogens. In the present work, we have explored the effect of externally added AHLs on in vitro oral biofilm models for commensal, cariogenic, and periodontal dental plaque. While little effect on bacterial growth was observed, some AHLs specifically affected the lactic acid production and protease activity of the biofilms. Most importantly, the analysis of bacterial diversity in the biofilms showed that the addition of C6-homoserine lactone (C6-HSL) results in a shift toward a periodontal bacterial composition profile by increasing the relative presence of the orange-complex bacteria Peptostreptococcus and Prevotella. These results point to a relevant role of AHL-mediated QS in dental plaque formation and might be involved in the development of dysbiosis, the mechanism of which should be further investigated. This finding potentially opens new opportunities for the prevention or treatment of the periodontal disease. IMPORTANCE Dental plaque is omnipresent in healthy oral cavities and part of our commensal microbial colonization. At the same time, dental plaque is the cause of the most common human diseases, caries and gum disease. Dental plaque consists of billions of microbes attached to the surface of your teeth. Communication among these microbes is pivotal for development of these complex communities yet poorly studied in dental plaque. In the present study, we show that a specific communication molecule induces changes within the community related to the development of gum disease. This finding suggests tha