Epigenome-wide Association Study for Tic Disorders in Children: A Preliminary Study in Korean Population.

Objective: : Tic disorders can affect the quality of life in both childhood and adolescence. Many factors are involved in the etiology of tic disorders, and the genetic and epigenetic factors of tic disorders are considered complex and heterogeneous. Methods: : In this study, the differentially methylated regions (DMRs) between normal controls (n = 24; aged 6-15; 7 females) and patients with tic disorders (n = 16; aged 6-15; 5 females) were analyzed. We performed an epigenome-wide association study of tic disorders in Korean children. The tics were assessed using Yale Global Tic Severity Scale. The DNA methylation data consisted of 726,945 cytosine phosphate guanine (CpG) sites, assessed using the Illumina Infinium MethylationEPIC (850k) BeadChip. The DNA methylation data of the 40 participants were retrieved, and DMRs between the four groups based on sex and tic disorder were identified. From 28 male and 16 female samples, 37 and 38 DMRs were identified, respectively. We analyzed the enriched terms and visualized the network, heatmap, and upset plot. Results: : In male, Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis revealed hypomethylated patterns in the ligand, receptor, and second signal transductors of the PI3K-Akt and MAPK signaling pathway (most cells were indicated as green color), and in female, the opposite patterns were revealed (most cells were indicated as red color). Five mental disorder-related enriched terms were identified in the network analysis. Conclusion: : Here, we provide insights into the epigenetic mechanisms of tic disorders. Abnormal DNA methylation patterns are associated with mental disorder-related symptoms.

Exploring oral bacterial compositional network in two oral disease groups using a convergent approach of NGS-molecular diagnostics.

BACKGROUND: Since most of the commonly known oral diseases are explained in link with balance of microbial community, an accurate bacterial taxonomy profiling for determining bacterial compositional network is essential. However, compared to intestinal microbiome, research data pool related to oral microbiome is small, and general 16S rRNA screening method has a taxonomy misclassification issue in confirming complex bacterial composition at the species level. OBJECTIVE: Present study aimed to explore bacterial compositional networks at the species level within saliva of 39 oral disease patients (Dental Caries group: n = 26 and Periodontitis group: n = 13) through comparison with public Korean-specific healthy oral microbiome data. METHODS: Here, we applied comprehensive molecular diagnostics based on qRT-PCR and Sanger sequencing methods to complement the technical limitations of NGS-based 16S V3-V4 amplicon sequencing technology. RESULTS: As a result of microbiome profiling at the genus level, relative frequencies of many nitrate-reducing bacteria within each oral disease group were found to be significantly low compared to the healthy group. In addition, the molecular diagnostics-based bacterial identification method allowed the determination of the correct taxonomy of screened primary colonizers (Streptococcus and Actinomyces unclassification clusters) for each oral disease. Finally, as with the results of microbiome profiling at the genus level, many core-species classified within the saliva of each oral disease group were also related to nitrate-reduction, and it was estimated that various pathogens associated with each disease formed a bacterial network with the core-species. CONCLUSION: Our study introduced a novel approach that can compensate for the difficulty of identifying an accurate bacterial compositional network at the species level due to unclear taxonomy classification by using the convergent approach of NGS-molecular diagnostics. Ultimately, we suggest that our experimental approach and results could be potential reference materials for researchers who intend to prevent oral disease by determining the correlation between oral health and bacterial compositional network according to the changes in the relative frequency for nitrate-reducing species.

Understanding the bacterial compositional network associations between oral and gut microbiome within healthy Koreans.

Oral microbial ecosystem could influence intestinal diseases, but there have been insufficient studies demonstrating the association of microbial composition between the oral cavity and the intestinal system. Thus, we aimed to investigate the compositional network within the oral microbiome related to gut enterotype from saliva and stool samples collected from 112 healthy Korean subjects. Here, we performed bacterial 16S amplicon sequencing from clinical samples. Then, we determined oral microbiome type related to individual's gut enterotype for healthy Korean. The co-occurrence analysis was performed to interactivity prediction of microbiome within saliva samples. As a result, it could be classified into two Korean oral microbiome types (KO) and four oral-gut-associated microbiome types (KOGA) according to distribution and significant differences of oral microflora. The co-occurrence analysis showed various bacterial compositional networks linked around Streptococcus and Haemophilus within healthy subjects. The present study was first approach in healthy Koreans to identify the oral microbiome types related to the gut microbiome and investigate their characteristics. Hence, we suggest that our results could be potential healthy control data for identifying differences in microbial composition between healthy people and oral disease patients and studying microbial association with the gut microbial environment (oral-gut microbiome axis).

A qRT-PCR Method Capable of Quantifying Specific Microorganisms Compared to NGS-Based Metagenome Profiling Data.

Metagenome profiling research using next-generation sequencing (NGS), a technique widely used to analyze the diversity and composition of microorganisms living in the human body, especially the gastrointestinal tract, has been actively conducted, and there is a growing interest in the quantitative and diagnostic technology for specific microorganisms. According to recent trends, quantitative real-time PCR (qRT-PCR) is still a considerable technique in detecting and quantifying bacteria associated with the human oral and nasal cavities, due to the analytical cost and time burden of NGS technology. Here, based on NGS metagenome profiling data produced by utilizing 100 gut microbiota samples, we conducted a comparative analysis for the identification and quantification of five bacterial genera (Akkermansia, Bacteroides, Bifidobacterium, Phascolarctobacterium, and Roseburia) within same metagenomic DNA samples through qRT-PCR assay in parallel. Genus-specific primers, targeting the particular gene of each genus for qRT-PCR assay, allowed a statistically consistent quantification pattern with the metagenome profiling data. Furthermore, results of bacterial identification through Sanger validation demonstrated the high genus-specificity of each primer set. Therefore, our study suggests that an approach to quantifying specific microorganisms by applying the qRT-PCR method can compensate for the concerns (potential issues) of NGS while also providing efficient benefits to various microbial industries.

A classification approach for genotyping viral sequences based on multidimensional scaling and linear discriminant analysis.

BACKGROUND: Accurate classification into genotypes is critical in understanding evolution of divergent viruses. Here we report a new approach, MuLDAS, which classifies a query sequence based on the statistical genotype models learned from the known sequences. Thus, MuLDAS utilizes full spectra of well characterized sequences as references, typically of an order of hundreds, in order to estimate the significance of each genotype assignment. RESULTS: MuLDAS starts by aligning the query sequence to the reference multiple sequence alignment and calculating the subsequent distance matrix among the sequences. They are then mapped to a principal coordinate space by multidimensional scaling, and the coordinates of the reference sequences are used as features in developing linear discriminant models that partition the space by genotype. The genotype of the query is then given as the maximum a posteriori estimate. MuLDAS tests the model confidence by leave-one-out cross-validation and also provides some heuristics for the detection of 'outlier' sequences that fall far outside or in-between genotype clusters. We have tested our method by classifying HIV-1 and HCV nucleotide sequences downloaded from NCBI GenBank, achieving the overall concordance rates of 99.3% and 96.6%, respectively, with the benchmark test dataset retrieved from the respective databases of Los Alamos National Laboratory. CONCLUSIONS: The highly accurate genotype assignment coupled with several measures for evaluating the results makes MuLDAS useful in analyzing the sequences of rapidly evolving viruses such as HIV-1 and HCV. A web-based genotype prediction server is available at http://www.muldas.org/MuLDAS/.

Changes in microbiome and metabolomic profiles of fecal samples stored with stabilizing solution at room temperature: a pilot study.

The gut microbiome is related to various host health conditions through metabolites produced by microbiota. Investigating their relationships involves association analysis of the population-level microbiome and metabolome data, which requires the appropriate collection, handling, and storage of specimens. Simplification of the specimen handling processes will facilitate such investigations. As a pilot study for population-level studies, we collected the fecal samples from three volunteers and tested whether a single sample collection procedure, particularly using OMNIgene-GUT, can be used to reliably obtain both microbiome and metabolome data. We collected fecal samples from three young and healthy Korean adults, stored them at room temperature with and without OMNIgene-GUT solution up to three weeks, and analyzed their microbiome and metabolite profiles. We found that the microbiome profiles were stably maintained in OMNIgene-GUT solution for 21 days, and the abundance relationships among metabolites were well preserved, although their absolute abundances slightly varied over time. Our results show that a single sampling procedure suffices to obtain a fecal sample for collecting gut microbiome and gut metabolome data of an individual. We expect that the health effects of gut microbiome via fecal metabolites can be further understood by increasing the sampling size to the population level.

Association between the relative abundance of gastric microbiota and the risk of gastric cancer: a case-control study.

The human gut hosts a diverse community of bacteria referred to as the gut microbiome. We investigated the association between the relative abundance of gastric microbiota and gastric cancer (GC) risk in a Korean population. The study participants included 268 GC patients and 288 controls. DNA was extracted from gastric biopsies, and 16S rRNA gene analysis was performed. Unconditional logistic regression models were used to observe the associations. Of the participants, those who had the highest level (highest tertile) of relative Helicobacter pylori and Propionibacterium acnes abundances showed a significantly higher risk for GC after adjusting for potential confounding variables (odds ratio (OR) = 1.86, 95% confidence interval (CI) = 1.17-2.97, p for trend = 0.017 and OR = 4.77, 95% CI = 2.94-7.74, p for trend <0.001, respectively). Subjects who carried Prevotella copri had a significantly higher risk of GC than noncarriers (OR = 2.54, 95% CI = 1.42-4.55, p for trend = 0.002). There was a lower risk of GC in subjects carrying Lactococcus lactis than in noncarriers (OR = 0.21, 95% CI = 0.10-0.44, p for trend <0.001). H. pylori, P. acnes and P. copri are strong risk factors, whereas L. lactis is a protective factor, for GC development in Koreans. Further microbiome studies are warranted to verify the findings of the current study.