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Deep metagenomics examines the oral microbiome during dental caries, revealing novel taxa and co-occurrences with host molecules.

ABSTRACT: Dental caries, the most common chronic infectious disease worldwide, has a complex etiology involving the interplay of microbial and host factors that are not completely understood. In this study, the oral microbiome and 38 host cytokines and chemokines were analyzed across 23 children with caries and 24 children with healthy dentition. De novo assembly of metagenomic sequencing obtained 527 metagenome-assembled genomes (MAGs), representing 150 bacterial species. Forty-two of these species had no genomes in public repositories, thereby representing novel taxa. These new genomes greatly expanded the known pangenomes of many oral clades, including the enigmatic Saccharibacteria clades G3 and G6, which had distinct functional repertoires compared to other oral Saccharibacteria. Saccharibacteria are understood to be obligate epibionts, which are dependent on host bacteria. These data suggest that the various Saccharibacteria clades may rely on their hosts for highly distinct metabolic requirements, which would have significant evolutionary and ecological implications. Across the study group, Rothia, Neisseria, and Haemophilus spp. were associated with good dental health, whereas Prevotella spp., Streptococcus mutans, and Human herpesvirus 4 (Epstein-Barr virus [EBV]) were more prevalent in children with caries. Finally, 10 of the host immunological markers were significantly elevated in the caries group, and co-occurrence analysis provided an atlas of potential relationships between microbes and host immunological molecules. Overall, this study illustrated the oral microbiome at an unprecedented resolution and contributed several leads for further study that will increase the understanding of caries pathogenesis and guide therapeutic development.

SUBMITTER: Baker JL

PROVIDER: S-EPMC7849383 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:With the aging of the population, dental caries in the elderly has received increasing attention. A comprehensive study of the oral microbiome is required to understand its polymicrobial etiology. The results of previous studies are limited and remain controversial. In this study, subjects 60 years and older with and without caries were recruited. Unstimulated saliva and dental plaque were collected from each subject and the bacterial 16S rDNA was amplified using PCR and sequenced by Illumina MiSeq high-throughput sequencing. A total of 92 samples were collected from 24 caries patients and 22 healthy controls. Sequences clustered into 147,531 OTUs, representing 16 phyla, 29 classes, 49 orders, 79 families, 149 genera, and 305 species. All predominant phyla, including Proteobacteria, Bacteroidetes, Firmicutes, Fusobacteria, Actinobacteria, and Saccharibacteria, were largely consistent in different groups, but different relative abundances could be observed. The core microbiome was defined with 246 shared species among groups, which occupied 80.7% of all the species detected. Alpha diversity showed no significant differences in bacterial richness or diversity between caries patients and healthy controls, but distinction existed between samples collected from dental plaque and saliva. Beta diversity analysis was performed by PCoA and hierarchical clustering analysis, showing similar results that microorganisms vary between the two niches. The biomarkers of different groups were defined by LEfSe analysis to identify potential caries-related and health-related bacteria. The co-occurrence analysis of the predominant genera revealed significant interactions among oral microbiota and exhibited more complex and aggregated bacterial correlations in caries-free groups. Finally, the functional prediction of the microbiota present in oral samples was performed by PICRUSt, indicating vigorous microbial metabolism in the oral bacterial community. Our study provides thorough knowledge of the microbiological etiology of elderly individuals with caries and is expected to provide novel methods for its prevention and treatment.

Project description:ObjectivesThis study aimed to investigate the accuracy of deep learning algorithms to diagnose tooth caries and classify the extension and location of dental caries in cone beam computed tomography (CBCT) images. To the best of our knowledge, this is the first study to evaluate the application of deep learning for dental caries in CBCT images.MethodsThe CBCT image dataset comprised 382 molar teeth with caries and 403 noncarious molar cases. The dataset was divided into a development set for training and validation and test set. Three images were obtained for each case, including axial, sagittal, and coronal. The test dataset was provided to a multiple-input convolutional neural network (CNN). The network made predictions regarding the presence or absence of dental decay and classified the lesions according to their depths and types for the provided samples. Accuracy, sensitivity, specificity, and F1 score values were measured for dental caries detection and classification.ResultsThe diagnostic accuracy, sensitivity, specificity, and F1 score for caries detection in carious molar teeth were 95.3%, 92.1%, 96.3%, and 93.2%, respectively, and for noncarious molar teeth were 94.8%, 94.3%, 95.8%, and 94.6%. The CNN network showed high sensitivity, specificity, and accuracy in classifying caries extensions and locations.ConclusionsThis research demonstrates that deep learning models can accurately identify dental caries and classify their depths and types with high accuracy, sensitivity, and specificity. The successful application of deep learning in this field will undoubtedly assist dental practitioners and patients in improving diagnostic and treatment planning in dentistry.Clinical significanceThis study showed that deep learning can accurately detect and classify dental caries. Deep learning can provide dental caries detection accurately. Considering the shortage of dentists in certain areas, using CNNs can lead to broader geographic coverage in detecting dental caries.

Project description:IntroductionA lower prevalence of dental caries (hereafter termed "caries") has been observed in children with dental extrinsic black stain (EBS).MethodsWe investigated the epidemiologic characterization of EBS and explored the possible role of the oral microbiome (OM) and gut microbiome (GM) in EBS formation and caries prevention. In an epidemiologic survey, 2,675 children aged 3-6 years were included. Thirty-eight of these children (7 children had both caries and EBS, 10 had EBS only, 11 had caries only, and 10 were healthy children) were recruited for 16S rRNA sequencing and collection of samples of supragingival plaque and feces. Collected plaque samples were divided into four groups: BCP (EBS+, caries+), BP (EBS+, caries-), CP (EBS-, caries+), and P (EBS-, caries-). Fecal samples were also divided into four groups: BCF (EBS+, caries+), BF (EBS+, caries-), CF (EBS-, caries+), and F (EBS-, caries-).ResultsEBS was observed in 12.10% of this population. Children with EBS had a significantly reduced prevalence of caries and a lower mean value of decayed-missing-filled teeth (dmft; p < 0.01). According to analyses of dental plaque, the P group had the most complex microbiome. The BCP group exhibited greater operational taxonomic unit (OTU) richness but a reduced evenness compared with the BP group, and the CP group showed greater OTU richness than the BP group. At the genus level, higher abundance of Actinomyces and Cardiobacterium species was observed in the BCP group. Higher abundance of Lautropia and Pesudopropionibacteriumin species was observed in the BP group compared with P and CP groups, respectively (p < 0.05). Veillonella species were significantly more common in P and CP groups than in BP groups, whereas Porphyromonas and Fusobacterium species were more common in the CP group (p < 0.05). With regard to the GM, the CF group exhibited greater OTU diversity than the BF group. The GM in the BCF group exhibited the most complex relationships across all fecal groups. GM groups could be distinguished by various unique biomarkers, such as Escherichia and Shigella species in the BCF group, Agathobacter and Ruminococcus species in the CF group, Lactobacillus species in the BF group, and Roseburia species in the F group. Our results suggest that EBS is a possible protective factor against early-childhood caries. Dental plaque and the GM may be relevant to EBS in primary dentition.

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Deep metagenomics examines the oral microbiome during dental caries, revealing novel taxa and co-occurrences with host molecules.

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