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The incidence of breast cancer (BC) is increasing in South Korea, and diet is closely related to the high prevalence of BC. The microbiome directly reflects eating habits. In this study, a diagnostic algorithm was developed by analyzing the microbiome patterns of BC. Blood samples were collected from 96 patients with BC and 192 healthy controls. Bacterial extracellular vesicles (EVs) were collected from each blood sample, and next-generation sequencing (NGS) of bacterial EVs was performed. Microbiome analysis of patients with BC and healthy controls identified significantly higher bacterial abundances using EVs in each group and confirmed the receiver operating characteristic (ROC) curves. Using this algorithm, animal experiments were performed to determine which foods affect EV composition. Compared to BC and healthy controls, statistically significant bacterial EVs were selected from both groups, and a receiver operating characteristic (ROC) curve was drawn with a sensitivity of 96.4%, specificity of 100%, and accuracy of 99.6% based on the machine learning method. This algorithm is expected to be applicable to medical practice, such as in health checkup centers. In addition, the results obtained from animal experiments are expected to select and apply foods that have a positive effect on patients with BC. [ABSTRACT FROM AUTHOR]

Background: Probiotics have been shown to prevent various allergic diseases by producing extracellular vesicles (EVs). However, the role of EVs in allergic asthma has not yet been completely determined. Methods: Gut microbial composition, mainly genera related to probiotics, was investigated in allergic asthmatic mice. Moreover, EVs were isolated from Lactococcus lactis (L. lactis, a selected bacterium) and EV proteins were identified by peptide mass fingerprinting. EV functions in immune responses were evaluated in vivo or ex vivo. Furthermore, the levels of specific IgG antibodies (an alternative marker for EV quantification) to L. lactis‐EVs were measured by ELISA in the sera of 27 asthmatic patients and 26 healthy controls. Results: Allergic asthmatic mice showed a lower proportion of Lactococcus compared to healthy mice. L. lactis was cultured and its EVs abundantly contained pyruvate kinase. When allergic asthmatic mice were intranasally treated with EVs, airway hyperresponsiveness, eosinophil number, cytokine secretion, and mucus production were significantly decreased. Moreover, L. lactis‐EV treatment shifted immune responses from Th2 to Th1 by stimulating dendritic cells to produce IL‐12. In addition, significantly lower levels of serum specific IgG4 (but not IgG1) to L. lactis‐EVs were noted in asthmatic patients than in healthy controls. A positive correlation between the levels of EV‐specific IgG4 and FEV1 (%), but a negative correlation between the levels of EV‐specific IgG4 and IL‐13 were observed. Conclusion: These findings suggest that L. lactis‐EVs may have immune‐regulating effects on airway inflammation mediated by dendritic cell activation, providing a potential benefit for allergic asthma. [ABSTRACT FROM AUTHOR]

The human microbiota comprises trillions of microbes, and the relationship between cancer and microbiota is very complex. The impact of fecal microbiota alterations on colorectal cancer (CRC) pathogenesis is emerging. This study analyzed changes in the microbial composition in CRC subjects with both fecal microbiota and gut microbe-derived extracellular vesicles (EVs). From August 2017 to August 2018, 70 CRC patients and 158 control subjects were enrolled in the study. Metagenomic profiling of fecal microbiota and gut microbe-derived EVs in stool was performed using 16S ribosomal DNA sequencing. Relative abundance, evenness, and diversity in both the gut microbiota and gut microbe-derived EVs were analyzed. Additionally, microbial composition changes according to the stage and location of CRC were analyzed. Microbial composition was significantly changed in CRC subjects compared to control subjects, with evenness and diversity significantly lower in the fecal microbiota of CRC subjects. Gut microbe-derived EVs of stool demonstrated significant differences in the microbial composition, evenness, and diversity in CRC subjects compared to the control subjects. Additionally, microbial composition, evenness, and diversity significantly changed in late CRC subjects compared to early CRC subjects with both fecal microbiota and gut microbe-derived EVs. Alistipes- derived EVs could be novel biomarkers for diagnosing CRC and predicting CRC stages. Ruminococcus 2-derived EVs significantly decreased in distal CRC subjects than in proximal CRC subjects. Gut microbe-derived EVs in CRC had a distinct microbial composition compared to the controls. Profiling of microbe-derived EVs may offer a novel biomarker for detecting and predicting CRC prognosis. [ABSTRACT FROM AUTHOR]

There is increasing evidence supporting the association between gut microbiome composition and mood disorders; however, studies on the circulating microbiome are scarce. This study aimed to analyze the association of the serum microbial DNA composition with depressive and anxiety symptoms in patients with mood disorders. The sera of 69 patients with mood disorders, aged from 19 to 60, were analyzed. Bacterial DNA was isolated from extracellular membrane vesicles and, subsequently, amplified and quantified with specific primers for the V3–V4 hypervariable region of the 16S rDNA gene. Sequence reads were clustered into Operational Taxonomic Units and classified using the SILVA database. There were no significant associations between alpha diversity measures and the total Hamilton depression rating scale (HAM-D) or Beck anxiety inventory (BAI) scores. Only the weighted UniFrac distance was associated with the total HAM-D score (F = 1.57, p = 0.045). The Bacteroidaceae family and Bacteroides genus were negatively associated with the total HAM-D score (β = − 0.016, p < 0.001, q = 0.08 and β = − 0.016, p < 0.001, q = 0.15, respectively). The Desulfovibrionaceae family and Clostridiales Family XIII were positively associated with the total BAI score (β = 1.8 × 10−3, p < 0.001, q = 0.04 and β = 1.3 × 10−3, p < 0.001, q = 0.24, respectively). Further studies with larger sample sizes and longitudinal designs are warranted. [ABSTRACT FROM AUTHOR]

Introduction: Microbial ecology is reported to be an important regulator of energy homeostasis and glucose metabolism. Microbes secrete extracellular vesicles (EVs) during their proliferation and death to communicate with other cells. To investigate the roles of gut microbiota in glucose metabolism, we analyzed serial changes of gut microbe and microbial EV composition before and after bariatric/metabolic surgery (BMS). Methods: Twenty-eight Wistar rats were fed on high-fat diet (HFD) to induce obesity and diabetes. Five of them compared with 5 rats fed on regular chow diet (RCD). Among the remaining 23 rats, Roux-en-Y gastric bypass (RYGB) (n = 10), sleeve gastrectomy (SG) (n = 10), or sham operation (n = 3) was randomly performed. Gut microbiota and EVs from fecal samples were analyzed by 16S rDNA amplicon sequencing. Results: The present study showed that microbial diversity was decreased in HFD-fed rats versus RCD-fed rats. In addition, BMS reversed glucose intolerance and microbial richness which were induced by HFD. In terms of microbiota and microbial EV composition, both RYGB and SG enhance the composition of phyla Proteobacteria, Verrucomicrobia, and their secreting EVs, but decrease phylum Firmicutes and its EVs. We tried to demonstrate specific genera showed a significant compositional difference in obesity/diabetes-induced rats compared with normal rats and then restored similarly toward normal rats' level after BMS. At the genus level, Lactococcus, Ruminococcus, Dorea in Firmicutes(p), Psychrobacter in Proteobacteria(p), and Akkermansia in Verrucomicrobia(p) fit these conditions after BMS. Conclusion: We suggest that these genera are the candidates contributing to obesity and diabetes improvement mechanism after BMS. [ABSTRACT FROM AUTHOR]

Lactobacillus paracasei has been known to reduce airway resistance and inflammation in asthma. However, the therapeutic effect of its extracellular vesicles (EVs) in patients with asthma remains unclear. To validate the clinical relevance of L. paracasei -derived EVs (LpEV) in asthma, the composition of gut microbial EVs was verified by metagenomics in LPS-induced C57BL/6 mice. The components of proteins and metabolites in LpEV were identified by peptide mass fingerprinting and metabolomic analysis. The serum levels of specific IgG1 or IgG4 antibodies to LpEV were compared by ELISA between patients with eosinophilic asthma (EA, n = 10) and those with neutrophilic asthma (NA, n = 10) as well as with healthy controls (HCs, n = 10). Finally, therapeutic effects of LpEV and their metabolites in asthma were validated in vivo / in vitro. Significantly lower proportions of EVs derived from Lactobacillus at the genus level were noted in mice with NA than in control mice. Moreover, the serum levels of LpEV-specific IgG4, but not IgG1, were lower in patients with NA than in those with EA or in HCs and positively correlated with FEV 1 (%) values. In addition, oral administration of LpEV reduced airway resistance and inflammation in mice with NA. Finally, LpEV and their 3 metabolites (dodecanoic acid, palmitoleic acid, and D-(−)-tagatose) significantly inhibited JNK phosphorylation/IL-8 production in airway epithelium in vitro. These findings suggest that LpEV may have a therapeutic potential targeting NA by suppressing the JNK pathway and proinflammatory cytokine production in airway epithelium. [ABSTRACT FROM AUTHOR]

Gut microbiota play an important part in the pathogenesis of mucosal inflammation, such as inflammatory bowel disease (IBD). However, owing to the complexity of the gut microbiota, our understanding of the roles of commensal and pathogenic bacteria in the maintenance of immune homeostasis in the gut is evolving only slowly. Here, we evaluated the role of gut microbiota and their secreting extracellular vesicles (EV) in the development of mucosal inflammation in the gut. Experimental IBD model was established by oral application of dextran sulfate sodium (DSS) to C57BL/6 mice. The composition of gut microbiota and bacteria-derived EV in stools was evaluated by metagenome sequencing using bacterial common primer of 16S rDNA. Metagenomics in the IBD mouse model showed that the change in stool EV composition was more drastic, compared to the change of bacterial composition. Oral DSS application decreased the composition of EV from Akkermansia muciniphila and Bacteroides acidifaciens in stools, whereas increased EV from TM7 phylum, especially from species DQ777900_s and AJ400239_s. In vitro pretreatment of A. muciniphila-derived EV ameliorated the production of a pro-inflammatory cytokine IL-6 from colon epithelial cells induced by Escherichia coli EV. Additionally, oral application of A. muciniphila EV also protected DSS-induced IBD phenotypes, such as body weight loss, colon length, and inflammatory cell infiltration of colon wall. Our data provides insight into the role of gut microbiota-derived EV in regulation of intestinal immunity and homeostasis, and A. muciniphila-derived EV have protective effects in the development of DSS-induced colitis. [ABSTRACT FROM AUTHOR]

Simple Summary: Gastric cancer shows an improved prognosis when diagnosed in its early stage. However, non-invasive diagnostic markers for gastric cancer known to date have poor clinical efficacies. Many studies have shown that gastric cancer patients have distinct microbial changes compared to normal subjects. In the present study, we performed metagenome analysis using body fluid samples (gastric juice, blood, and urine) to investigate the distinct microbial composition using bacteria-derived EVs from gastric cancer patients. We could build diagnostic prediction models for gastric cancer with the metagenomic data and analyzed the accuracy of models. Although further validation is required to apply these findings to real clinical practice yet, our study showed the possibility of gastric cancer diagnosis with the integration of liquid biopsy and metagenome analysis. Early detection is crucial for improving the prognosis of gastric cancer, but there are no non-invasive markers for the early diagnosis of gastric cancer in real clinical settings. Recently, bacteria-derived extracellular vesicles (EVs) emerged as new biomarker resources. We aimed to evaluate the microbial composition in gastric cancer using bacteria-derived EVs and to build a diagnostic prediction model for gastric cancer with the metagenome data. Stool, urine, and serum samples were prospectively collected from 453 subjects (gastric cancer, 181; control, 272). EV portions were extracted from the samples for metagenome analysis. Differences in microbial diversity and composition were analyzed with 16S rRNA gene profiling, using the next-generation sequencing method. Biomarkers were selected using logistic regression models based on relative abundances at the genus level. The microbial composition of healthy groups and gastric cancer patient groups was significantly different in all sample types. The compositional differences of various bacteria, based on relative abundances, were identified at the genus level. Among the diagnostic prediction models for gastric cancer, the urine-based model showed the highest performance when compared to that of stool or serum. We suggest that bacteria-derived EVs in urine can be used as novel metagenomic markers for the non-invasive diagnosis of gastric cancer by integrating the liquid biopsy method and metagenome analysis. [ABSTRACT FROM AUTHOR]