• Journal of dental hygiene science
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• v.19 no.2
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• pp.77-85
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• 2019

In the past gut microbiome has been the main focus of microbiome research. Studies about the microbiome inside oral cavities and other organs are underway. Studies about the relationship between noninfectious diseases and periodontal diseases, and the negative effects of harmful oral microbes on systemic health have been published in the recent past. A lot of attention is being paid towards fostering a healthy oral microbial ecosystem. This study aimed to understand the roles and effects of the microbiome inside the human body can potentially help cure various diseases including inflammatory bowel diseases with no known cure such as Crohn's disease, atopic dermatitis, obesity, cancer, diabetes, brain diseases and oral diseases. The present study examined technological trends in the correlation between the human microbiome and diseases in the human body, interactions between the human body's immunity, the metabolic system, and the microbiome, and research trends in other countries. While it has been proven that human microbiome is closely correlated with human diseases, most studies are still in the early stage of trying to compare the composition of microbiomes between health and patient groups. Since the oral environment is a dynamic environment that changes due to not only food intake but also other external factors such as lifestyle, hygiene, and drug intake, it is necessary to continue in-depth research on the microbiome composition characteristics to understand the complex functions of oral microorganisms. Analyzing the oral microbiome using computational technology may aid in disease diagnosis and prevention.

• BMB Reports
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• v.49 no.12
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• pp.662-670
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• 2016

The human oral cavity contains a highly personalized microbiome essential to maintaining health, but capable of causing oral and systemic diseases. Thus, an in-depth definition of "healthy oral microbiome" is critical to understanding variations in disease states from preclinical conditions, and disease onset through progressive states of disease. With rapid advances in DNA sequencing and analytical technologies, population-based studies have documented the range and diversity of both taxonomic compositions and functional potentials observed in the oral microbiome in healthy individuals. Besides factors specific to the host, such as age and race/ethnicity, environmental factors also appear to contribute to the variability of the healthy oral microbiome. Here, we review bioinformatic techniques for metagenomic datasets, including their strengths and limitations. In addition, we summarize the interpersonal and intrapersonal diversity of the oral microbiome, taking into consideration the recent large-scale and longitudinal studies, including the Human Microbiome Project.

• International Journal of Oral Biology
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• v.45 no.3
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• pp.77-83
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• 2020

In the oral cavity, complex microbial community is shaped by various host and environmental factors. Extensive literature describing the oral microbiome in the context of oral health and disease is available. Advances in DNA sequencing technologies and data analysis have drastically improved the analysis of the oral microbiome. For microbiome study, bacterial 16S ribosomal RNA gene amplification and sequencing is often employed owing to the cost-effective and fast nature of the method. In this review, practical considerations for performing a microbiome study, including experimental design, molecular analysis technology, and general data analysis, will be discussed.

• Microbiology and Biotechnology Letters
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• v.48 no.4
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• pp.574-581
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• 2020

Next generation sequencing is commonly used to characterize the microbiome structure. MiSeq is commonly used to analyze the microbiome due to its relatively long read length. However, recently, Illumina introduced the 250x2 chip for HiSeq 2500. The purpose of this study was to compare the performance of MiSeq and HiSeq in the context of oral microbiome samples. The MiSeq Reagent Kit V3 and the HiSeq Rapid SBS Kit V2 were used for MiSeq and HiSeq 2500 analyses, respectively. Total read count, read quality score, relative bacterial abundance, community diversity, and relative abundance correlation were analyzed. HiSeq produced significantly more read sequences and assigned taxa compared to MiSeq. Conversely, community diversity was similar in the context of MiSeq and HiSeq. However, depending on the relative abundance, the correlation between the two platforms differed. The correlation between HiSeq and MiSeq sequencing data for highly abundant taxa (> 2%), low abundant taxa (2-0.2%), and rare taxa (0.2% >) was 0.994, 0.860, and 0.416, respectively. Therefore, HiSeq 2500 may also be compatible for microbiome studies. Importantly, the HiSeq platform may allow a high-resolution massive parallel sequencing for the detection of rare taxa.

• BMB Reports
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• v.56 no.1
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• pp.15-23
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• 2023

After birth, animals are colonized by a diverse community of microorganisms. The digestive tract is known to contain the largest number of microbiome in the body. With emergence of the gut-brain axis, the importance of gut microbiome and its metabolites in host health has been extensively studied in recent years. The establishment of organoid culture systems has contributed to studying intestinal pathophysiology by replacing current limited models. Owing to their architectural and functional complexity similar to a real organ, co-culture of intestinal organoids with gut microbiome can provide mechanistic insights into the detrimental role of pathobiont and the homeostatic function of commensal symbiont. Here organoid-based bacterial co-culture techniques for modeling host-microbe interactions are reviewed. This review also summarizes representative studies that explore impact of enteric microorganisms on intestinal organoids to provide a better understanding of host-microbe interaction in the context of homeostasis and disease.

• Journal of Gastric Cancer
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• v.24 no.1
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• pp.89-98
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• 2024

This review delved into the intricate relationship between the gastrointestinal microbiome and gastric cancer, particularly focusing on post-treatment alterations, notably following gastrectomy, and the effects of anticancer therapies. Following gastrectomy, analysis of fecal samples revealed an increased presence of oral cavity aerotolerant and bile acid-transforming bacteria in the intestine. Similar changes were observed in the gastric microbiome, highlighting significant alterations in taxon abundance and emphasizing the reciprocal interaction between the oral and gastric microbiomes. In contrast, the impact of chemotherapy and immunotherapy on the gut microbiome was subtle, although discernible differences were noted between treatment responders and non-responders. Certain bacterial taxa showed promise as potential prognostic markers. Notably, probiotics emerged as a promising approach for postgastrectomy recovery, displaying the capacity to alleviate inflammation, bolster immune responses, and maintain a healthy gut microbiome. Several strains, including Bifidobacterium, Lactobacillus, and Clostridium butyricum, exhibited favorable outcomes in postoperative patients, suggesting their potential roles in comprehensive patient care. In conclusion, understanding the intricate interplay between the gastrointestinal microbiome and gastric cancer treatment offers prospects for predicting responses and enhancing postoperative recovery. Probiotics, with their positive impact on inflammation and immunity, have emerged as potential adjuncts in patient care. Continued research is imperative to fully harness the potential of microbiome-based interventions in the management of gastric cancer.

• Journal of Oral Medicine and Pain
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• v.47 no.1
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• pp.10-26
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• 2022

Purpose: The purpose of this study was to investigate whether various saliva collection methods affect the observed salivary microbiome and whether microbiomes of stimulated and unstimulated saliva and plaque differ in richness and diversity. Methods: Seven sampling methods for unstimulated saliva, stimulated saliva, and plaque samples were applied to six orally and systemically healthy participants. Bacterial 16S ribosomal RNA genes of 10 major oral bacterial species, namely, Aggregatibacter actinomycetemcomitans, Porphyromonas gingivalis, Tannerella forsythia, Treponema denticola, Fusobacterium nucleatum, Prevotella intermedia, Prevotella nigrescens, Streptococcus mitis, Streptococcus sobrinus, and Lactobacillus casei, were analyzed by real-time polymerase chain reaction. We comprehensively examined the dependence of the amount of bacterial ribosomal DNA (rDNA), bacterial-community composition, and relative abundance of each species on sample collection methods. Results: There were significant differences in the bacterial rDNA copy number depending on the collection method in three species: F. nucleatum, P. nigrescens, and S. mitis. The species with the highest richness was S. mitis, with the range from 89.31% to 100.00%, followed by F. nucleatum, P. nigrescens, T. denticola, T. forsythia, and P. intermedia, and the sum of the proportions of the remaining five species was less than 1%. The species with the lowest observed richness was P. gingivalis (<0.1%). The Shannon diversity index was the highest in unstimulated saliva collected with a funnel (4.449). The Shannon diversity index was higher in plaque samples (3.623) than in unstimulated (3.171) and stimulated (3.129) saliva and in mouthwash saliva samples (2.061). Conclusions: The oral microbial profile of saliva samples can be affected by sample collection methods, and saliva differs from plaque in the microbiome. An easy and rapid technique for saliva collection is desirable; however, observed microbial-community composition may more accurately reflect the actual microbiome when unstimulated saliva is assayed.

• Journal of Periodontal and Implant Science
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• v.53 no.3
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• pp.233-244
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• 2023

Purpose: An implant-supported prosthesis consists of an implant fixture, an abutment, an internal screw that connects the abutment to the implant fixture, and the upper prosthesis. Numerous studies have investigated the microorganisms present on the implant surface, surrounding tissues, and the subgingival microflora associated with peri-implantitis. However, there is limited information regarding the microbiome within the internal screw space. In this study, microbial samples were collected from the supragingival surfaces of natural teeth, the peri-implant sulcus, and the implant-abutment screw hole, in order to characterize the microbiome of the internal screw space in healthy subjects. Methods: Samples were obtained from the supragingival region of natural teeth, the peri-implant sulcus, and the implant screw hole in 20 healthy subjects. DNA was extracted, and the V3-V4 region of the 16S ribosomal RNA was sequenced for microbiome analysis. Alpha diversity, beta diversity, linear discriminant analysis effect size (LEfSe), and network analysis were employed to compare the characteristics of the microbiomes. Results: We observed significant differences in beta diversity among the samples. Upon analyzing the significant taxa using LEfSe, the microbial composition of the implant-abutment screw hole's microbiome was found to be similar to that of the other sampling sites' microbiomes. Moreover, the microbiome network analysis revealed a unique network complexity in samples obtained from the implant screw hole compared to those from the other sampling sites. Conclusions: The bacterial composition of the biofilm collected from the implant-abutment screw hole exhibited significant differences compared to the supra-structure of the implant. Therefore, long-term monitoring and management of not only the peri-implant tissue but also the implant screw are necessary.

• Journal of the Korean Association of Oral and Maxillofacial Surgeons
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• v.44 no.2
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• pp.41-42
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• 2018

• Journal of dental hygiene science
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• v.19 no.2
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• pp.86-95
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• 2019

The modern era of microbial genome analysis began in earnest in the 2000s with the generalization of metagenomics and gene sequencing techniques. Studying complex microbial community such as oral cavity and colon by a pure culture is considerably ineffective in terms of cost and time. Therefore, various techniques for genomic analysis have been developed to overcome the limitation of the culture method and to explore microbial communities existing in the natural environment at the gene level. Among these, DNA fingerprinting analysis and microarray chip have been used extensively; however, the most recent method of analysis is metagenomics. The study summarily examined the overview of metagenomics analysis techniques, as well as domestic and foreign studies on disease genomics and cluster analysis related to oral metagenome. The composition of oral bacteria also varies across different individuals, and it would become possible to analyze what change occurs in the human body depending on the activity of bacteria living in the oral cavity and what causality it has with diseases. Identification, isolation, metabolism, and presence of functional genes of microorganisms are being identified for correlation analysis based on oral microbial genome sequencing. For precise diagnosis and treatment of diseases based on microbiome, greater effort is needed for finding not only the causative microorganisms, but also indicators at gene level. Up to now, oral microbial studies have mostly involved metagenomics, but if metatranscriptomic, metaproteomic, and metabolomic approaches can be taken together for assessment of microbial genes and proteins that are expressed under specific conditions, then doing so can be more helpful for gaining comprehensive understanding.