Exploration of Potential Gut Microbiota-Derived Biomarkers to Predict the Success of Fecal Microbiota Transplantation in Ulcerative Colitis: A Prospective Cohort in Korea.

Background/Aims: Although fecal microbiota transplantation (FMT) has been proven as one of the promising treatments for patients with ulcerative colitis (UC), potential prognostic markers regarding the clinical outcomes of FMT remain elusive. Methods: We collected fecal samples of 10 participants undergoing FMT to treat UC and those from the corresponding donors. We categorized them into two groups: responders and nonresponders. Sequencing of the bacterial 16S rRNA gene was conducted on the samples to explore bacterial composition. Results: Analyzing the gut microbiota of patients who showed different outcomes in FMT presented a distinct microbial niche. Source tracking analysis showed the nonresponder group had a higher rate of preservation of donor microbiota, underscoring that engraftment degrees are not one of the major drivers for the success of FMT. At the phylum level, Bacteroidetes bacteria were significantly depleted (p<0.003), and three genera, including Enterococcus, Rothia, and Pediococcus, were enriched in the responder group before FMT (p=0.003, p=0.025, and p=0.048, respectively). Furthermore, we applied a machine learning algorithm to build a prediction model that might allow the prediction of FMT outcomes, which yielded an area under the receiver operating characteristic (ROC) curve of 0.844. Notably, the microbiota-based model was much better at predicting outcomes than the clinical features model (area under the ROC curve=0.531). Conclusions: This study is the first to suggest the significance of indigenous microbiota of recipients as a critical factor. The result highlights that bacterial composition should be evaluated before FMT to select suitable patients and achieve better efficiency.

Bacterial Profiles of Brain in Downer Cattle with Unknown Etiology.

Downer cow can be caused by muscular paralysis, neurological damage, metabolic disorder, and/or the complication of microbial infection. However, downer cow with unknown etiology is issued because of the non-detection of its bacterial etiological agent. In this study, differences in the bacterial community in brain tissues between downer cattle with unknown etiology and healthy slaughtered cattle are investigated. Bacterial diversity and representative genera between downer and normal cattle were significantly different (p < 0.05). There are significant differences in representative genera of downer and normal cattle, especially the significance, fold change, and area under the receiver operating characteristic curve score (p < 0.05). Furthermore, the prediction of functional genes in brain microbiota between the downer and normal cattle revealed differences in the cluster of orthologous gene categories, such as lipid transport and metabolism, secondary metabolite biosynthesis, and signal transduction (p < 0.05). This study revealed a significant difference in microbiota between the downer and normal cattle. Thus, we demonstrate that representative genera from downer cattle through 16S rRNA gene amplicon sequencing and microbiota analysis have the potential as candidates for bacterial etiological agents for downer cow.

Alteration of the Soil Microbiota in Ginseng Rusty Roots: Application of Machine Learning Algorithm to Explore Potential Biomarkers for Diagnostic and Predictive Analytics.

Conceptualization to utilize microbial composition as a prediction tool has been widely applied in human cohorts, yet the potential capacity of soil microbiota as a diagnostic tool to predict plant phenotype remains unknown. Here, we collected 130 soil samples which are 54 healthy controls and 76 ginseng rusty roots (GRRs). Alpha diversities including Shannon, Simpson, Chao1, and phylogenetic diversity were significantly decreased in GRR (P < 0.05). Moreover, we identified 30 potential biomarkers. The optimized markers were obtained through fivefold cross-validation on a support vector machine and yielded a robust area under the curve of 0.856. Notably, evaluation of multi-index classification performance including accuracy, F1-score, and Kappa coefficient also showed robust discriminative capability (90.99%, 0.903, and 0.808). Taken together, our results suggest that the disease affects the microbial community and offers the potential ability of soil microbiota to identifying farms at the risk of GRR.

Potential Association between Vaginal Microbiota and Cervical Carcinogenesis in Korean Women: A Cohort Study.

Convincing studies demonstrated that vaginal flora is one of the most impactful key components for the well-being of the genital tract in women. Nevertheless, the potential capability of vaginal-derived bacterial communities as biomarkers to monitor cervical carcinogenesis (CC) has yet to be studied actively compared to those of bacterial vaginosis (BV). We hypothesized that vaginal microbiota might be associated with the progression of CC. In this study, we enrolled 23 participants, including healthy controls (HC group; n = 7), patients with cervical intraepithelial neoplasia (CIN) 2 and 3 (CIN group, n = 8), and patients with invasive cervical cancer (CAN group; n = 8). Amplicon sequencing was performed using the Ion Torrent PGM to characterize the vaginal microbiota. Patients with CIN and CAN presented vaginal microbiota dysbiosis compared with HC. The alpha diversity analysis revealed that CC has a trend to be increased in terms of diversity indexes. Moreover, CC was associated with the abundance of specific microbes, of which Lactobacillus and Gardnerella were the most significantly different between HC and CIN, whereas Streptococcus was differentially abundant in CAN compared with CIN. We then evaluated their diagnostic abilities. Testing in terms of diagnostic ability using the three genera revealed considerably high performance with an area under the receiver-operating characteristic curve of 0.982, 0.953, and 0.922. The current study suggests that the presence of Gardnerella and Streptococcus may be involved in the advancment of CC.

Dynamics of Fecal Microbiota with and without Invasive Cervical Cancer and Its Application in Early Diagnosis.

The fecal microbiota is being increasingly implicated in the diagnosis of various diseases. However, evidence on changes in the fecal microbiota in invasive cervical cancer (ICC) remains scarce. Here, we aimed to investigate the fecal microbiota of our cohorts, develop a diagnostic model for predicting early ICC, and identify potential fecal microbiota-derived biomarkers using amplicon sequencing data. We obtained fecal samples from 29 healthy women (HC) and 17 women with clinically confirmed early ICC (CAN). Although Shannon's diversity index was not reached at statistical significance, the Chao1 and Observed operational taxonomic units (OTUs) in fecal microbiota was significantly different between CAN and HC group. Furthermore, there were significant differences in the taxonomic profiles between HC and CAN; Prevotella was significantly more abundant in the CAN group and Clostridium in the HC group. Linear discriminant analysis effect size (LEfSe) analysis was applied to validate the taxonomic differences at the genus level. Furthermore, we identified a set of seven bacterial genera that were used to construct a machine learning (ML)-based classifier model to distinguish CAN from patients with HC. The model had high diagnostic utility (area under the curve [AUC] = 0.913) for predicting early ICC. Our study provides an initial step toward exploring the fecal microbiota and helps clinicians diagnose.

Vaginal Microbiome-Based Bacterial Signatures for Predicting the Severity of Cervical Intraepithelial Neoplasia.

Although emerging evidence revealed that the gut microbiome served as a tool and as biomarkers for predicting and detecting specific cancer or illness, it is yet unknown if vaginal microbiome-derived bacterial markers can be used as a predictive model to predict the severity of CIN. In this study, we sequenced V3 region of 16S rRNA gene on vaginal swab samples from 66 participants (24 CIN 1-, 42 CIN 2+ patients) and investigated the taxonomic composition. The vaginal microbial diversity was not significantly different between the CIN 1- and CIN 2+ groups. However, we observed Lactobacillus amylovorus dominant type (16.7%), which does not belong to conventional community state type (CST). Moreover, a minimal set of 33 bacterial species was identified to maximally differentiate CIN 2+ from CIN 1- in a random forest model, which can distinguish CIN 2+ from CIN 1- (area under the curve (AUC) = 0.952). Among the 33 bacterial species, Lactobacillus iners was selected as the most impactful predictor in our model. This finding suggests that the random forest model is able to predict the severity of CIN and vaginal microbiome may play a role as biomarker.

Irradiation-Induced Intestinal Damage Is Recovered by the Indigenous Gut Bacteria Lactobacillus acidophilus.

The intestinal tract is one of the most sensitive organs following irradiation. The protective effect of specific indigenous microbiota on irradiation-induced damage to intestinal epithelial cells has not been reported. Mice were irradiated with a single dose of 6 Gy of gamma rays. The intestinal damage was analyzed by histopathology. Intestinal stemness and differentiation were determined by intestinal organoid culture. Microbiota community was observed by high-throughput 16S rRNA gene sequencing and oligotyping analysis. We showed that distal small intestine was damaged by sublethal dose of gamma irradiation. Intestinal organoids derived from the irradiated mice showed defects in budding and mucin expression, suggesting the detrimental effect of irradiation on the intestinal stemness and differentiation. In addition, irradiation reduced intestinal immunoglobulin A level, concomitant with decreased microbiota diversity based on our high-throughput 16S rRNA gene sequencing data. Especially, the relative abundance of Lactobacillus was reduced at early time point post-irradiation; however, it was recovered at late time point. Oligotyping analysis within the Lactobacillus genus indicated that Lactobacillus-related oligotype 1 (OT1) including Lactobacillus acidophilus might drive recovery after irradiation as it was associated with increased long-term numbers post-exposure. We showed that treatment with heat-killed L. acidophilus rescued the budding-impaired organoids and induced sufficient differentiation in epithelial cells, and particularly mucin-producing cells, in intestinal organoids. This study provides the first evidence that the indigenous gut bacteria L. acidophilus enhance intestinal epithelial function with respect to irradiation-induced intestinal damage by improving intestinal stem cell function and cell differentiation.

In Situ Profiling of the Three Dominant Phyla Within the Human Gut Using TaqMan PCR for Pre-Hospital Diagnosis of Gut Dysbiosis.

A microbial imbalance called dysbiosis leads to inflammatory bowel disease (IBD), which can include ulcerative colitis (UC). Fecal microbiota transplantation (FMT), a novel therapy, has recently been successful in treating gut dysbiosis in UC patients. For the FMT technique to be successful, the gut microbiota of both the healthy donors and UC patients must be characterized. For decades, next-generation sequencing (NGS) has been used to analyze gut microbiota. Despite the popularity of NGS, the cost and time constraints make it difficult to use in emergency services and activities related to the periodic monitoring of microbiota profile alterations. Hence, in this study, we developed a multiplex TaqMan qPCR assay (MTq-PCR) with novel probes to simultaneously determine the relative proportions of the three dominant microbial phyla in the human gut: Bacteroidetes, Firmicutes, and Proteobacteria. The relative proportions of the three phyla in fecal samples of either healthy volunteers or UC patients were similar when assessed NGS and the MTq-PCR. Thus, our MTq-PCR assay could be a practical microbiota profiling alternative for diagnosing and monitoring gut dysbiosis in UC patients during emergency situations, and it could have a role in screening stool from potential FMT donors.

Characterisation and microbial community analysis of lipid utilising microorganisms for biogas formation.

In the anaerobic process, fat-oil-grease (FOG) is hydrolysed to long-chain fatty acids (LCFAs) and glycerol (GLYC), which are then used as substrates to produce biogas. The increase in FOG and LCFAs inhibits methanogenesis, and so far, most work investigating this inhibition has been carried out when FOG or LCFAs were used as co-substrates. In the current work, the inhibition of methanogenesis by FOG, LCFAs and GLYC was investigated when used as sole substrates. To gain more insight on the dynamics of this process, the change of microbial community was analysed using 16S rRNA gene amplicon sequencing. The results indicate that, as the concentrations of cooking olive oil (CO, which represents FOG) and LCFAs increase, methanogenesis is inhibited. For instance, at 0.01 g. L-1 of FOG, the rate of biogas formation was around 8 ml.L-1.day-1, and this decreased to <4 ml.L-1.day-1 at 40 g.L-1. Similar results were observed with the use of LCFAs. However, GLYC concentrations up to 100g.L-1 did not affect the rate of biogas formation. Acidic pH, temperature > = 45°C and NaCl > 3% led to a significant decrease in the rate of biogas formation. Microbial community analyses were carried out from samples from 3 different bioreactors (CO, OLEI and GLYC), on day 1, 5 and 15. In each bioreactor, microbial communities were dominated by Proteobacteria, Firmicutes and Bacteroidetes phyla. The most important families were Enterobacteriaceae, Pseudomonadaceae and Shewanellaceae (Proteobacteria phylum), Clostridiacea and Ruminococcaceae (Firmicutes) and Porphyromonadaceae and Bacteroidaceae (Bacteroidetes). In CO bioreactor, Proteobacteria bacteria decreased over time, while those of OLEI and GLYC bioreactors increased. A more pronounced increase in Bacteroidetes and Firmicutes were observed in CO bioreactor. The methanogenic archaea Methanobacteriaceae and Methanocorpusculaceae were identified. This analysis has shown that a set of microbial population is selected as a function of the substrate.

The first complete mitochondrial genome sequence of the korean endemic catfish Silurus microdorsalis (Actinopteri, Siluriformes, Siluridae).

The Silurus microdorsalis is known as Korean endemic slender catfish. Despite its value as a biological resource, there is no complete mitochondrial genome sequence. The complete mitochondrial genome consisted of 16,524 bp including 22 transfer RNA (tRNAs), 2 ribosomal RNA (rRNAs), 13 protein-coding genes (PCGs), and A + T rich region. The overall base composition of S. microdorsalis was A + T: 56.1%, C + G: 43.9%, apparently with slight AT bias. Phylogenetic relationship showed that S. microdorsalis was closely related to Silurus glanis.