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Saliva influences the release of aroma in the oral cavity. The composition of human saliva varies depending on stimulation and host's origin; however, the compositional differences of saliva and their influences on aroma release have not been fully evaluated. In this study, we recruited 30 healthy adults (15 Australians and 15 Chinese) and collected saliva samples at three stages: before, during, and after stimulation. Salivary samples were characterized by the flow rate, total protein concentration, esterase activity, microbiome composition by full-length 16S rRNA gene sequencing, and the ability to release aroma from wine by headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC-MS). Differences in salivary composition and specific wine volatiles were found between Australian and Chinese participants and among the three stimulation stages. Significant correlations between the relative abundance of 3 bacterial species and 10 wine volatiles were observed. Our results confirm the influence of participant's geographic origin and stimulation on the salivary composition, highlighting the role of salivary components, especially salivary bacteria, on the release of aroma from wine.

Globally, early childhood caries (ECC) is a significant public health concern, necessitating effective prediction and prevention strategies. This study aimed to explore variations in the oral microbiome of saliva from pre-school Han and Uyghur children during ECC development and establish a predictive model based on temporal oral microbiome changes. Saliva samples were collected from a single kindergarten every three months over six months. Forty-four pre-school children provided 132 samples, categorized into six groups: (1) HEF (healthy pre-school Han children), (2) HEO (Han children with caries), (3) HEP (Han children with progressive caries), (4) WEF (healthy pre-school Uyghur children), (5) WEO (Uyghur children with caries), and (6) WEP (Uyghur children with progressive caries). Illumina Miseq sequencing identified oral microbiome differences between groups and time points. The Random Forest (RF) algorithm established ECC prediction models. The T1HEO group exhibited significantly higher Chaol index, observed species index, PD whole tree index, and Shannon index than the T2HEO group ( p < 0.01). Similarly, the T1WEO group had significantly higher Chaol index, observed species index, and PD whole tree index than the T2WEO group ( p < 0.05). The AUROC value for the ECC prediction model based on temporal oral flora changes was 0.517 (95% CI: 0.275-0.759) for pre-school Han children and 0.896 (95% CI: 0.78-1.00) for pre-school Uyghur children. In the onset of caries in pre-school Han children, bacterial species richness and community diversity in saliva declined, paralleled by a decrease in bacterial species richness in pre-school Uyghur children's oral saliva. The ECC prediction model grounded on temporal oral microflora changes exhibited robust predictive power, particularly for pre-school Uyghur children, potentially leading to more effective ECC prevention measures., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (©2024 The Author(s). Published by MRE Press.)

Salivary bacterial community composition is associated with the host's internal and environmental factors, which have potential applications in forensic practice. The 16S rRNA gene sequencing is the most commonly used strategy for detecting salivary bacterial diversity; however, its platforms are not compatible with capillary electrophoresis (CE) platforms commonly used for forensic applications. Therefore, we attempted to detect the salivary bacterial diversity using a single nucleotide polymorphism (SNP) assay. Salivary bacterial diversity varies among diverse geographic locations, making it a potential supplementary biomarker for forensic geographic sourcing. To evaluate the performance of the multiplex SNaPshot assay, saliva samples from three geographic locations in China were analyzed using the multiplex SNaPshot assay and 16S rRNA gene sequencing. We screened SNPs from two high-relative-abundance salivary genera (Streptococcus and Veillonella) to construct a multiplex SNaPshot system that can be used on the CE platform. The stability and sensitivity of the multiplex SNaPshot system were also tested. A random forest classification model was used to classify samples from different regions to explore the ability of salivary bacteria to discriminate between geographic sources. Six bacterial SNPs were screened and a multiplex SNaPshot system was constructed. The stability results showed that the typing of salivary stains that were placed indoors for different days was not affected in this study. Two-thirds of mocked salivary stain samples showed more than 90% of typing results obtained for salivary stain samples with an input of 0.1 µl saliva. The results of principal coordinate analysis based on salivary bacterial diversity showed significant differences between samples from the three different geographic locations. The accuracy of the random forest classification was 66.67% based on the multiplex SNaPshot assay and 83.33% based on the 16S rRNA gene sequencing. In conclusion, this is the first attempt to detect salivary bacterial diversity using a multiplex SNaPshot bacterial SNP assay. The geographic difference in human salivary bacterial community composition was significant, as revealed by the multiplex SNaPshot assay; however, its performance in discriminating geographic sources was lower than that of 16S rRNA gene sequencing. This strategy based on bacterial SNP loci may favor the detection of human bacterial diversity in common forensic laboratories but requires further exploration in larger sample sizes and more bacterial SNP loci. • A primary exploration that uses a bacterial SNP assay to detect human salivary bacterial diversity • Screening six bacterial SNPs from Streptococcus and Veillonella genera, and constructing a multiplex SNaPshot system • The geographic difference in salivary bacteria was significant, as revealed by the SNPassay and 16S rRNA gene sequencing [ABSTRACT FROM AUTHOR]

High serum thyroid-stimulating hormone (TSH) levels are linked to many metabolic disorders, but the effects of TSH levels on the oral microbiota are still largely unknown. This study aimed to explore the association between the salivary microbiome in adults and serum TSH levels. Saliva and fasting blood samples were obtained from a health census conducted in Southeast China. All participants were divided according to serum TSH levels. The microbial genetic profiles and changes were acquired by 16S rDNA sequencing and bioinformatics analysis. Relevant anthropometric and biochemical measurements such as insulin resistance, blood lipids, and body composition were evaluated with laboratory tests and physical examinations. The salivary microbiome in individuals with higher TSH level showed significantly higher taxa diversity. Principal coordinates analysis and partial least squares discriminant analysis showed distinct clustering in the Abnormal and Normal Groups (Adonis, P =0.0320). Granulicatella was identified as a discriminative genus for comparison of the two groups. Fasting serum insulin, Homeostatic Model Assessment for Insulin Resistance, and hemoglobin A1 were elevated in the Abnormal Group ( P <0.05), showing the presence of insulin resistance in individuals with abnormal higher serum TSH levels. Distance-based redundancy analysis revealed the association of this distinctive difference with salivary microbiome. In conclusion, shifts in microbial profile were observed in the saliva of individuals with different serum TSH levels, and insulin resistance may play an important role in the biochemical and microbial alteration., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Dong, Zhao, Yuan, Zhu, Wang, Xia, Lu and Huang.)

The aim of this study was to investigate the variation of the salivary microbiota in the recurrence of early childhood caries (ECC), and to explore and verify the potential microbial indicators of ECC recurrence. Saliva samples from kindergarten children were tracked every 6 months for 1 year. Finally, in total 28 children and 84 samples were placed on the analysis phase: 7 children with ECC recurrence made up the ECC-recurrence (ER) group, 6 children without ECC recurrence constituted the non-ECC-recurrence (NER) group, and 15 children who kept ECC-free were set as the ECC-free (EF) group. DNA amplicons of the V3-V4 hypervariable region of the bacterial 16S rDNA were generated and sequencing was performed using Illumina MiSeq PE250 platform. No statistically significant differences of the Shannon indices were found in both cross-sectional and longitudinal comparisons. Furthermore, both principal coordinates analysis (PCoA) and heatmap plots demonstrated that the salivary microbial community structure might have potentiality to predict ECC recurrence at an early phase. The relative abundance of Fusobacterium, Prevotella, Leptotrichia , and Capnocytophaga differed significantly between the ER and NER groups at baseline. The values of area under the curve (AUC) of the four genera and their combined synthesis in the prediction for ECC recurrence were 0.857, 0.833, 0.786, 0.833, and 0.952, respectively. The relative abundance of Fusobacterium, Prevotella, Leptotrichia , and Capnocytophaga and their combination showed satisfactory accuracy in the prediction for ECC recurrence, indicating that salivary microbiome had predictive potentiality for recurrence of this disease. These findings might facilitate more effective strategy to be taken in the management of the recurrence of ECC.