Yong Ju Ahn

Introduction: The field of human microbiome research is rapidly expanding beyond the gut and into the facial skin care industry. However, there is still no established criterion to define the objective relationship between the microbiome and clinical trials for developing personalized skin solutions that consider individual diversity.Objectives: In this study, we conducted an integrated analysis of skin measurements, clinical Baumann skin type indicator (BSTI) surveys, and the skin microbiome of 950 Korean subjects to examine the ideal skin microbiome-biophysical associations.Methods: By utilizing four skin biophysical parameters, we identified four distinct Korean Skin Cutotypes (KSCs) and categorized the subjects into three aging groups: the Young (under 34 years old), the Aging I group (35-50), and the Old group (over 51). To unravel the intricate connection between the skin’s microbiome and KSC types, we conducted DivCom clustering analysis.Results: This endeavor successfully classified 726 out of 740 female skin microbiomes into three subclusters: DC1-sub1, DC1-sub2, and DC2 with 15 core genera. To further amplify our findings, we harnessed the potent capabilities of the CatBoost boosting algorithm and achieved a reliable framework for predicting skin types based on microbial composition with an impressive average accuracy of 0.96 AUC value. Our study conclusively demonstrated that these 15 core genera could serve as objective indicators, differentiating the microbial composition among the aging groups.Conclusion: In conclusion, this study sheds light on the complex relationship between the skin microbiome and biophysical properties, and the findings provide a promising approach to advance the field of skincare, cosmetics, and broader microbial research.

Inflammatory bowel disease (IBD) is a chronic condition characterized by intestinal inflammation and dysbiosis, with limited treatment options and significant challenges in long-term management. This study investigated the therapeutic potential of novel strains belonging to Bifidobacterium longum and Limosilactobacillus species, in a dextran sodium sulfate (DSS)–induced mouse model of colitis. In this study, our primary objective was to determine whether ingestion of these strains alleviates colitis symptoms and, if so, to elucidate how they restored gut microbial balance and modulated microbial metabolic functions. In most probiotic-treated groups, colitis disease activity index scores were significantly improved and colon length was preserved, with strains CBA7106 and BBH exhibiting efficacy comparable to that of the Lactobacillus rhamnosus GG (used as a positive control). Moreover, histological analyses confirmed reduced inflammation and enhanced mucosal integrity. Microbial diversity assessments demonstrated a marked restoration of gut microbial composition, highlighted by increased abundances of beneficial taxa such as Lactobacillus and Akkermansia. Metabolomic profiling identified key anti-inflammatory metabolites, including 6-hydroxycaproic acid, indole-3-lactic acid, and choline, which were significantly elevated in the probiotic-treated groups. Notably, functional analyses using PICRUSt2 revealed a sustained decrease in the siderophore biosynthesis pathway (ko01053), suggesting that these candidate probiotic strains may inhibit siderophore production—a pivotal mechanism by which pathogenic bacteria aggravate intestinal inflammation. Taken together, these findings indicate that the candidate probiotic strains CBA7106 and BBH effectively mitigate DSS-induced colitis by modulating the gut microbiota, promoting the production of anti-inflammatory metabolites, and suppressing siderophore biosynthesis. This study provides valuable insights into the development of targeted probiotic therapies for IBD, underscoring their potential as a complementary approach to restoring intestinal health and reducing inflammation. Further clinical studies are warranted to validate these observations in human populations.

The current approaches for detecting most colorectal polyps and early neoplasms lack sufficient sensitivity and specificity, potentially hindering treatment and ultimately reducing survival rates. Here, we performed a metagenomic analysis to identify microbiome markers in stool samples from patients with early-stage colorectal cancer (CRC). We compared the composition of gut microbiota between patients with CRC and healthy individuals, specifically focusing on patients with early-stage CRC, defined as those without core mutations (KRAS, BRAF) for CRC diagnosis, stable microsatellite instability, and distant metastasis. The aim of our study is to identify potential biomarkers from gut microbiota at different cancer stages in colorectal cancer (CRC) patients through 16S rRNA amplicon sequencing, thereby proposing a novel non-invasive method for the early diagnosis of CRC. Specific microbes were detected from groups divided based on the TNM criteria, with one group classified by tumour size only (named the T group) and another group with lymph node metastasis (named the TN group). Aerobic bacteria, such as Delftia, Stenotrophomonas, Sphingobacterium, Rhodococcus, Devosia, Ensifer, and Psychrobacter were predominantly detected in patients with CRC without lymph node metastasis. The diagnostic prediction was evaluated using the CatBoost algorithm; these microbes presented high diagnostic accuracy with a receiver operating characteristics-area under curve of 0.8, which was validated using qPCR. In conclusion, this study identified specific aerobic microbial groups as non-invasive biomarkers for early diagnosis in patients with CRC without genetic or environmental factors.

Background Obesity and diabetes mellitus (DM) have become public health concerns worldwide. Both conditions have severe consequences and are associated with significant medical costs and productivity loss. Additionally, Helicobacter pylori infection may be a risk factor for the development of these conditions. However, whether eradicating H. pylori infection directly causes weight loss or improves insulin sensitivity is unknown. Methods In this study, we confirmed the effect of sleeve gastrectomy according to the state of the gastric microbiota in 40 patients with obesity, DM, and H. pylori infection. Patients with obesity were divided into four groups: non-DM without H. pylori infection (ND), non-DM with H. pylori infection (ND-HP), DM, and DM with H. pylori infection (DM-HP) using 16S V3–V4 sequencing. Results In the DM group, ALT, hemoglobin, HbA1c, blood glucose, and HSI significantly decreased, whereas high-density lipoprotein significantly increased. However, in the H. pylori-positive group, no significant difference was observed. The diversity of gastric microbiota decreased in the order of the ND > DM > ND-HP > DM-HP groups. We also conducted a correlation analysis between the preoperative microbes and clinical data. In the ND-HP group, most of the top 20 gastric microbiota were negatively correlated with glucose metabolism. However, H. pylori infection was positively correlated with pre-insulin levels. Conclusion Therefore, these findings indicate that patients with obesity and diabetes clearly benefit from surgery, but H. pylori infection may also affect clinical improvement.

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.

Young Kyung Ko, Suhyuk Chi, Gyu-Hwi Nam, Kyung-Wan Baek, Kung Ahn, Yongju Ahn, June Kang, Moon-Soo Lee, Jeong-An Gim. Clin Psychopharmacol Neurosci 2024;22:295-305. https://doi.org/10.9758/cpn.23.1099

Obesity is considered a high-risk disease and a global epidemic, and the number of obese patients is rising at an alarming rate worldwide. High-fat diet-induced dysbiosis of the intestinal microbiota is considered an essential factor related to obesity. Bariatric surgery induces a sharp decrease in fat content and effectively improves the metabolism of obese individuals. Herein, we aimed to investigate the effects of a high-fat diet-induced obesity and the alterations in gastric and intestinal microbiota resulting from sleeve gastrectomy on clinical outcomes. We performed 16S sequencing of gastric and fecal samples obtained from rats in three treatment groups: normal chow diet, high-fat diet (HFD), and sleeve gastrectomy after HDF for 14 weeks. The area under the curve of fasting glucose and the levels of leptin and low-density lipoproteins were significantly different between groups. Microbial taxa that were highly correlated with several clinical parameters were identified for each group. Glyoxylate and dicarboxylate, taurine and hypotaurine, butanoate, nitrogen, and pyrimidine metabolism and aminoacyl-transfer ribonucleic acid biosynthesis were affected by bariatric surgery and were significantly associated with changes in the composition of gastric and fecal microbiomes. Connectivity and co-occurrence were higher in fecal samples than in gastric tissues. Our results elucidated the positive effects of sleeve gastrectomy in obesity and shed light on changes in the microbiomes of gastric and fecal samples.

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).

The human skin sebum suggests that it (along with other epidermal surface lipids) plays a role in skin barrier formation, the moderation of cutaneous inflammation, and antimicrobial defense. Various methods have been developed for collecting and measuring skin sebum. We tested methods of detection using “color intensity”, by staining the skin casual sebum. This process was conducted in three steps; first, the selection of materials for sebum collection; second, staining the collected sebum; third, the development of a device that can measure the level of stained sebum. A plastic film was used to effectively collect sebum that increased with the replacement time of the sebum. In addition, the collected sebum was stained with Oil Red O (ORO) and checked with RGB; as a result, the R² value was higher than 0.9. It was also confirmed that the correlation value was higher than 0.9 in the comparison result with Sebumeter^®, which is a common standard technology. Finally, it was confirmed that the R² value was higher than 0.9 in the detection value using the sensor. In conclusion, we have proven the proof of concept (PoC) for this method, and we would like to introduce an effective sebum measurement method that differs from the existing method.

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.