Alterations in gastric and gut microbiota following sleeve gastrectomy in high-fat diet-induced obese rats.

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.

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).

Comparison of the oral microbial composition between healthy individuals and periodontitis patients in different oral sampling sites using 16S metagenome profiling.

PURPOSE: The purpose of this study was to compare the microbial composition of 3 types of oral samples through 16S metagenomic sequencing to determine how to resolve some sampling issues that occur during the collection of sub-gingival plaque samples. METHODS: In total, 20 subjects were recruited. In both the healthy and periodontitis groups, samples of saliva and supra-gingival plaque were collected. Additionally, in the periodontitis group, sub-gingival plaque samples were collected from the deepest periodontal pocket. After DNA extraction from each sample, polymerase chain reaction amplification was performed on the V3-V4 hypervariable region on the 16S rRNA gene, followed by metagenomic sequencing and a bioinformatics analysis. RESULTS: When comparing the healthy and periodontitis groups in terms of alpha-diversity, the saliva samples demonstrated much more substantial differences in bacterial diversity than the supra-gingival plaque samples. Moreover, in a comparison between the samples in the case group, the diversity score of the saliva samples was higher than that of the supra-gingival plaque samples, and it was similar to that of the sub-gingival plaque samples. In the beta-diversity analysis, the sub-gingival plaque samples exhibited a clustering pattern similar to that of the periodontitis group. Bacterial relative abundance analysis at the species level indicated lower relative frequencies of bacteria in the healthy group than in the periodontitis group. A statistically significant difference in frequency was observed in the saliva samples for specific pathogenic species (Porphyromonas gingivalis, Treponema denticola, and Prevotella intermedia). The saliva samples exhibited a similar relative richness of bacterial communities to that of sub-gingival plaque samples. CONCLUSIONS: In this 16S oral microbiome study, we confirmed that saliva samples had a microbial composition that was more similar to that of sub-gingival plaque samples than to that of supra-gingival plaque samples within the periodontitis group.

A Real-Time Detection Device for the Rapid Quantification of Skin Casual Sebum Using the Oil Red O Staining Method.

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.

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.

The effect of taxonomic classification by full-length 16S rRNA sequencing with a synthetic long-read technology.

Characterizing the microbial communities inhabiting specimens is one of the primary objectives of microbiome studies. A short-read sequencing platform for reading partial regions of the 16S rRNA gene is most commonly used by reducing the cost burden of next-generation sequencing (NGS), but misclassification at the species level due to its length being too short to consider sequence similarity remains a challenge. Loop Genomics recently proposed a new 16S full-length-based synthetic long-read sequencing technology (sFL16S). We compared a 16S full-length-based synthetic long-read (sFL16S) and V3-V4 short-read (V3V4) methods using 24 human GUT microbiota samples. Our comparison analyses of sFL16S and V3V4 sequencing data showed that they were highly similar at all classification resolutions except the species level. At the species level, we confirmed that sFL16S showed better resolutions than V3V4 in analyses of alpha-diversity, relative abundance frequency and identification accuracy. Furthermore, we demonstrated that sFL16S could overcome the microbial misidentification caused by different sequence similarity in each 16S variable region through comparison the identification accuracy of Bifidobacterium, Bacteroides, and Alistipes strains classified from both methods. Therefore, this study suggests that the new sFL16S method is a suitable tool to overcome the weakness of the V3V4 method.