Metagenomic Analysis of Bacterial Community and Isolation of Representative Strains from Vranjska Banja Hot Spring, Serbia

The hot spring Vranjska Banja is the hottest spring on the Balkan Peninsula with a water temperature of 63-95 °C and a pH value of 7.1, in situ. According to the physicochemical analysis, Vranjska Banja hot spring belongs to the bicarbonated and sulfated hyperthermal waters. The structures of microbial community of this geothermal spring are still largely unexplored. In order to determine and monitor the diversity of microbiota of the Vranjska Banja hot spring, a comprehensive culture-independent metagenomic analysis was conducted in parallel with a culture-dependent approach for the first time. Microbial profiling using amplicon sequencing analysis revealed the presence of phylogenetically novel taxa, ranging from species to phyla. Cultivation-based methods resulted in the isolation of 17 strains belonging to the genera Anoxybacillus, Bacillus, Geobacillus, and Hydrogenophillus. Whole-genome sequencing of five representative strains was then performed. The genomic characterization and OrthoANI analysis revealed that the Vranjska Banja hot spring harbors phylogenetically novel species of the genus Anoxybacillus, proving its uniqueness. Moreover, these isolates contain stress response genes that enable them to survive in the harsh conditions of the hot springs. The results of the in silico analysis show that most of the sequenced strains have the potential to produce thermostable enzymes (proteases, lipases, amylases, phytase, chitinase, and glucanase) and various antimicrobial molecules that can be of great importance for industrial, agricultural, and biotechnological applications. Finally, this study provides a basis for further research and understanding of the metabolic potential of these microorganisms.

Characterization of Oral Microbiota Following Chemotherapy in Patients With Hematopoietic Malignancies

Oral microbiota may be associated with serious local or systemic medical conditions resulting from chemotherapy. This study was conducted to evaluate the changes in the oral microbiota following the initiation of chemotherapy in patients with hematopoietic malignancies and to identify the characteristics of the oral microbiota associated with oral mucositis. Oral samples were collected from 57 patients with hematopoietic malignancies at 2 time points: before the start of chemotherapy and 8 to 20 days after the start of chemotherapy, when chemotherapy-induced oral mucositis often occurs, and 16S rRNA metagenomic analyses were performed. Comparative and linear discriminant analysis effect size (LEfSe) analyses were used to determine the characteristic bacterial groups before and after the initiation of chemotherapy and in those who developed oral mucositis. The alpha and beta diversities of oral microbiota before and after the initiation of chemotherapy differed significantly (operational taxonomic unit index, P < .001; Shannon's index, P < .001; unweighted UniFrac distances, P = .001; and weighted UniFrac distances, P = .001). The LEfSe analysis revealed a group of bacteria whose abundance differed significantly before and after the initiation of chemotherapy. In the group of patients who developed oral mucositis, a characteristic group of bacteria was identified before the start of chemotherapy. In conclusion, we characterized the oral microbiota associated with the initiation of chemotherapy in patients with hematopoietic malignancies. In addition, our findings suggest that oral microbiota composition before the start of chemotherapy may be associated with oral mucositis. The results of this study emphasize the importance of oral management focusing on the oral microbiota during chemotherapy in patients with hematologic malignancies.

Salivary Microbiota Associated with Peripheral Microvascular Endothelial Dysfunction

AIMS

Oral health is associated with atherosclerotic cardiovascular disease (ACVD). We previously identified the salivary microbiota characteristics of patients with ACVD. However, whether salivary microbiota is characteristic under impaired vascular endothelial function before ACVD onset remains unclear. Therefore, we aimed to evaluate the characteristics of salivary microbiota associated with peripheral microvascular endothelial dysfunction.

METHODS

We collected saliva samples from 172 community-dwelling elderly individuals without a history of ACVD and performed 16S rRNA metagenomic analysis. We assessed the peripheral microvascular endothelial function using reactive hyperemia index (RHI) and compared the salivary microbiota in the groups with normal (RHI ≥ 2.10), borderline, and abnormal (RHI ＜1.67) peripheral endothelial function. Furthermore, we applied machine learning techniques to evaluate whether salivary microbiota could discriminate between individuals with normal and abnormal endothelial function.

RESULTS

The number of operational taxonomic units (OTUs) was higher in the abnormal group than in the normal group (p=0.037), and differences were found in the overall salivary microbiota structure (unweighted UniFrac distances, p=0.038). The linear discriminant analysis (LDA) effect size (LEfSe) algorithm revealed several significantly differentially abundant bacterial genera between the two groups. An Extra Trees classifier model was built to discriminate between groups with normal and abnormal vascular endothelial function based on the microbial composition at the genus level (AUC=0.810).

CONCLUSIONS

The salivary microbiota in individuals with endothelial dysfunction was distinct from that in individuals with normal endothelial function, indicating that the salivary microbiota may be related to endothelial function.

Characterization of salivary microbiota in elderly patients with type 2 diabetes mellitus: a matched case-control study

OBJECTIVE

The importance of oral health in type 2 diabetes mellitus (T2DM) is widely recognized; however, oral microbiota characteristics associated with T2DM in the elderly population are not well-understood. This study was conducted to evaluate the characteristics of the salivary microbiota in elderly Japanese patients with T2DM.

METHODS

Saliva samples were collected from 42 elderly Japanese patients with T2DM and 42 age- and sex-matched subjects without T2DM (control). 16S ribosomal RNA metagenomic analysis and comparative analysis of both groups were performed. Random forest classification by machine learning was performed to discriminate between the salivary microbiota in the two groups.

RESULTS

There were significant differences in the overall salivary microbiota structure between the T2DM and control groups (beta diversity; unweighted UniFrac distances, p = 0.001; weighted UniFrac distances, p = 0.001). The phylum Firmicutes was abundant in patients with T2DM, whereas the phylum Bacteroidetes was abundant in controls. The T2DM prediction model by random forest based on salivary microbiota data was verified with a high predictive potential in five cross-validation tests (area under the curve (AUC) = 0.938 (95% CI, 0.824-1.000)).

CONCLUSION

Characterization revealed that the salivary microbiota profile of the elderly patients with T2DM is significantly distinct from that of the controls.

CLINICAL RELEVANCE

These data indicate the necessity of oral health management based on the characteristics of the salivary microbiota in elderly patients with T2DM. Our findings will contribute to future research on the development of new diagnostic and therapeutic methods for this purpose.

Characterization of Salivary Microbiota in Patients with Atherosclerotic Cardiovascular Disease: A Case-Control Study

Aims: Oral bacteria have been reported to be associated with the pathogenesis of atherosclerosis; however, the relationship between the oral microbiota and atherosclerosis remains unclear. The present study aimed to investigate whether or not salivary microbiota of patients with atherosclerotic cardiovascular disease (ACVD) differs from that of subjects without ACVD, and to characterize the salivary microbiota of patients with ACVD.

Methods: This study included 43 patients with ACVD and 86 age- and sex-matched non-ACVD individuals. 16S rRNA metagenomic analysis were performed using DNA isolated from the saliva samples of the participants. To select unique operational taxonomic unit (OTU) sets of ACVD, we conducted the random forest algorithm in machine learning, followed by confirmation via 10-fold cross-validation

Results: There was no difference in richness or evenness between the ACVD and non-ACVD groups (alpha diversity; observed OTU index, p =0.503; Shannon’s index, p =0.478). However, significant differences were found in the overall salivary microbiota structure (beta diversity; unweighted UniFrac distances, p =0.001; weighted UniFrac distances, p =0.001). The Actinobacteria phylum was highly abundant in patients with ACVD, while the Bacteroidetes phylum was less abundant. The random forest classifier identified 43 OTUs as an optimal marker set of ACVD. In a 10-fold cross validation using the validation data, an area under the curve (AUC) of 0.933 (95% CI, 0.855–1.000) was obtained.

Conclusions: The salivary microbiota in patients with ACVD was distinct from that of non-ACVD individuals, indicating that the salivary microbiota may be related to ACVD.

Production, Structural Characterization, and In Vitro Assessment of the Prebiotic Potential of Butyl-Fructooligosaccharides

Short-chain fatty acids (SCFAs), especially butyrate, produced in mammalian intestinal tracts via fermentation of dietary fiber, are known biofunctional compounds in humans. However, the variability of fermentable fiber consumed on a daily basis and the diversity of gut microbiota within individuals often limits the production of short-chain fatty acids in the human gut. In this study, we attempted to enhance the butyrate levels in human fecal samples by utilizing butyl-fructooligosaccharides (B-FOS) as a novel prebiotic substance. Two major types of B-FOS (GF3-1B and GF3-2B), composed of short-chain fructooligosaccharides (FOS) bound to one or two butyric groups by ester bonds, were synthesized. Qualitative analysis of these B-FOS using Fourier transform infrared (FT-IR) spectroscopy, matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF-MS), nuclear magnetic resonance (NMR) and low-resolution fast-atom bombardment mass spectra (LR-FAB-MS), showed that the chemical structure of GF3-1B and GF3-2B were [O-(1-buty-β-D-fru-(2→1)-O-β-D-fru-(2→1)-O-β-D-fru-O-α-D-glu] and [O-(1-buty)-β-D-fru-(2→1)-O-β-D-fru-(2→1)-O-(4-buty)-β-D-fru-O-α-D-glu], respectively. The ratio of these two compounds was approximately 5:3. To verify their biofunctionality as prebiotic oligosaccharides, proliferation and survival patterns of human fecal microbiota were examined in vitro via 16S rRNA metagenomics analysis compared to a positive FOS control and a negative control without a carbon source. B-FOS treatment showed different enrichment patterns on the fecal microbiota community during fermentation, and especially stimulated the growth of major butyrate producing bacterial consortia and modulated specific butyrate producing pathways with significantly enhanced butyrate levels. Furthermore, the relative abundance of Fusobacterium and ammonia production with related metabolic genes were greatly reduced with B-FOS and FOS treatment compared to the control group. These findings indicate that B-FOS differentially promotes butyrate production through the enhancement of butyrate-producing bacteria and their metabolic genes, and can be applied as a novel prebiotic compound in vivo.