Title Page
Chapter 1 Abstract
제1장 국문초록
Chapter 2 Abstract
제2장 국문초록
Chapter 3 Abstract
제3장 국문초록
Contents
Chapter 1. A qRT-PCR method capable of quantifying specific microorganisms compared to NGS-based metagenome profiling data 22
1.1. Introduction 23
1.2. Materials and Methods 25
1.2.1. Human stool samples collection 25
1.2.2. Metagenomic DNA extraction 25
1.2.3. Illumina 16S V3-V4 amplicon sequencing library preparation and sequencing 25
1.2.4. Bacterial genus-specific primer design methods 26
1.2.5. Bacterial quantification using qRT-PCR 27
1.2.6. Sanger sequencing 27
1.2.7. 16S V3-V4 data processing and microbial community analysis 28
1.2.8. Statistical analysis 28
1.3. Results 29
1.3.1. Selection of five bacterial genera from 16S metagenome analysis data 29
1.3.2. Bacterial genus-specific primer design 30
1.3.3. Quantification and normalization of metagenomic DNA 32
1.3.4. Parallel comparison of qRT-PCR and 16S metagenome profiling data 34
1.3.5. Verification of primer specificity 37
1.4. Discussion 39
1.5. Supplements & Acknowledgements 41
1.5.1. Supplements & Data availability 41
1.5.2. Acknowledgements 41
1.6. References 42
Chapter 2. Understanding the bacterial compositional network associations between oral and gut microbiome within healthy Koreans 47
2.1. Introduction 48
2.2. Materials and Methods 49
2.2.1. Clinical information of participants in this study 49
2.2.2. Clinical sample collection and metagenomic DNA extraction 49
2.2.3. Illumina library construction and 16S V3-V4 sequencing 50
2.2.4. 16S microbiome data analysis 50
2.2.5. Microbiome type clustering 51
2.2.6. Compare with public oral microbiome data in other nations 51
2.2.7. Co-occurrence and correlation analysis 51
2.2.8. LEfSe analysis 52
2.2.9. Scoring for characterization of KOGA type 52
2.2.10. Statistical analysis 52
2.3. Results 53
2.3.1. 16S metagenomic sequencing data processing of two different clinical sample types 53
2.3.2. Clustering of healthy Korean oral microbiome type 53
2.3.3. Determining healthy Korean oral-gut-associated oral microbiome type 55
2.3.4. Inference of bacterial compositional network within each oral microbiome type 58
2.3.5. Characterization of KOGA type 62
2.4. Discussion 66
2.5. Supplements & Acknowledgements 68
2.5.1. Supplements & Data availability 68
2.5.2. Acknowledgements 68
2.6. References 69
Chapter 3. Exploring oral bacterial compositional network in two oral disease groups using a convergent approach of NGS-molecular diagnostics 72
3.1. Introduction 73
3.2. Materials and Methods 74
3.2.1. Clinical information of two oral disease groups in this study 74
3.2.2. Clinical sample collection and Illumina platform-based 16S metagenomic sequencing 74
3.2.3. Bioinformatic approach for comprehensive microbiome study 75
3.2.4. Comparison of bacterial genera frequency using molecular genetical approach 75
3.2.5. Statistical analysis 77
3.2.6. Data availability of cited and applied public data (healthy control data) for comparative microbiome study 78
3.3. Results and Discussion 79
3.3.1. Clinical parameters of subjects 79
3.3.2. Pre-processing of 16S V3-V4 metagenome sequencing data for comprehensive microbiome analysis 79
3.3.3. Comparison of oral microbial diversity between each disease and healthy groups 81
3.3.4. Comparison of oral bacterial community at genus level between each disease and healthy group 85
3.3.5. Molecular diagnostics approach-based identification of primary colonizer related to each oral disease 89
3.3.6. Association between each oral disease and nitrate reduction-based bacterial compositional network 93
3.4. Conclusions 96
3.5. Supplements & Acknowledgements 97
3.5.1. Supplements & Data availability 97
3.5.2. Acknowledgements 97
3.6. References 98
Summary 103
VITA 105
Research Ethics Education Certificate 108
Chapter 1. A qRT-PCR method capable of quantifying specific microorganisms compared to NGS-based metagenome profiling data 20
Table 1.1. Overall information of bacterial genus-specific primer set 31
Table 1.2. Average standard curve calculation results using qRT-PCR assay 33
Table 1.3. Statistical result of the Spearman correlation test between two different quantification methods. 36
Table 1.4. Bacterial identification result by Sanger sequencing 38
Chapter 2. Understanding the bacterial compositional network associations between oral and gut microbiome within healthy Koreans 20
Table 2.1. Clinical information of experimental participant group 49
Table 2.2. Compositional network between bacterial genera within S type. 59
Table 2.3. Compositional network between bacterial genera within H type 60
Table 2.4. Distinct bacterial taxa exported from LEfSe analysis between each KOGA type 61
Table 2.5. Distribution of each bacterial species based on z-score calculation 65
Chapter 3. Exploring oral bacterial compositional network in two oral disease groups using a convergent approach of NGS-molecular diagnostics 20
Table 3.1. Overall clinical information of present study 80
Table 3.2. Average alpha-diversity calculation statics about oral microbiome data compared to KOGA type 84
Table 3.3. Beta-diversity calculation statics about oral microbiome data compared to KOGA type 84
Table 3.4. Comparison of relative frequency for top 10 oral bacterial genera within each oral disease group with KOGA type 88
Table 3.5. Comparison of relative bacterial frequency between control and oral disease group via qRT-PCR 92
Chapter 1. A qRT-PCR method capable of quantifying specific microorganisms compared to NGS-based metagenome profiling data 18
Figure 1.1. Experimental introduction in this study and schematic workflow of genus-specific primer design method for qRT-PCR assay. 29
Figure 1.2. Standard curve calculation to confirm normalization of the mDNA concentration used for qRT-PCR analysis. 32
Figure 1.3. Parallel comparison of the five bacterial genera proportions measured from two different quantification methods 34
Figure 1.4. Spearman correlation scatter plot showing the relationship of each bacterial relative proportion 35
Chapter 2. Understanding the bacterial compositional network associations between oral and gut microbiome within healthy Koreans 18
Figure 2.1. Data processing for clustering KO type using PAM clustering method 54
Figure 2.2. Data process of KOGA type clustering and comparison with national oral microbiome data. 56
Figure 2.3. Comparison with oral microbiome data of other nations annotated on the public database. 57
Figure 2.4. Heatmap plot and table showing the distribution of beneficial and harmful bacteria within oral samples of each KOGA type through scoring method 63
Figure 2.5. Heatmap plot and table showing the distribution of beneficial and harmful bacteria within gut samples of each KOGA type through scoring method 64
Chapter 3. Exploring oral bacterial compositional network in two oral disease groups using a convergent approach of NGS-molecular diagnostics 19
Figure 3.1. Box plots showing results of microbial alpha-diversity comparisons with the control group for each oral disease group 82
Figure 3.2. Principal Coordinate analysis (PCoA) plots showing results of microbial beta-diversity comparisons with the control group for each oral disease group 83
Figure 3.3. Bar plots representing comparison results of relative bacterial abundance 87
Figure 3.4. Relative abundance bar plots and box plots showing the relative frequency differences 91
Figure 3.5. Schematic diagram showing the nitrate-reducing bacteria-derived bacterial compositional network at the species level within each oral disease type CS8) insertion-mediated deletion in the chimpanzee genome. 95