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The biodiversity Composition of Microbiome in Ovarian Carcinoma Patients.

ABSTRACT: Ovarian carcinoma is caused by multiple factors, but its etiology associated with microbes and infection is unknown. Using 16S rRNA high-throughput sequencing methods, the diversity and composition of the microbiota from ovarian cancer tissues (25 samples) and normal distal fallopian tube tissues (25 samples) were analyzed. High-throughput sequencing showed that the diversity and richness indexes were significantly decreased in ovarian cancer tissues compared to tissues from normal distal fallopian tubes. The ratio of the two phyla for Proteobacteria/Firmicutes was notably increased in ovarian cancer, which revealed that microbial composition change might be associated with the process of ovarian cancer development. In addition, transcriptome-sequencing (RNA-seq) analyses suggested that the transcriptional profiles were statistically different between ovarian carcinoma and normal distal fallopian tubes. Moreover, a set of genes including 84 different inflammation-associated or immune-associated genes, which had been named as the human antibacterial-response genes were also modulated expression. Therefore, we hypothesize that the microbial composition change, as a novel risk factor, may be involving the initiation and progression of ovarian cancer via influencing and regulating the local immune microenvironment of fallopian tubes except for regular pathways.

SUBMITTER: Zhou B

PROVIDER: S-EPMC6368644 | biostudies-literature | 2019 Feb

REPOSITORIES: biostudies-literature

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The biodiversity Composition of Microbiome in Ovarian Carcinoma Patients.

Zhou Bo B Sun Chaoyang C Huang Jia J Xia Meng M Guo Ensong E Li Na N Lu Hao H Shan Wanying W Wu Yifan Y Li Yuan Y Xu Xiaoyan X Weng Danhui D Meng Li L Hu Junbo J Gao Qinglei Q Ma Ding D Chen Gang G

Scientific reports 20190208 1

Ovarian carcinoma is caused by multiple factors, but its etiology associated with microbes and infection is unknown. Using 16S rRNA high-throughput sequencing methods, the diversity and composition of the microbiota from ovarian cancer tissues (25 samples) and normal distal fallopian tube tissues (25 samples) were analyzed. High-throughput sequencing showed that the diversity and richness indexes were significantly decreased in ovarian cancer tissues compared to tissues from normal distal fallop ...[more]

PMID: 30737418

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Project description:BackgroundLower respiratory tract infection (LRTI) is a major contributor to respiratory failure requiring intubation and mechanical ventilation. LRTI also occurs during mechanical ventilation, increasing the morbidity and mortality of intubated patients. We sought to understand the dynamics of respiratory tract microbiota following intubation and the relationship between microbial community structure and infection.ResultsWe enrolled a cohort of 15 subjects with respiratory failure requiring intubation and mechanical ventilation from the medical intensive care unit at an academic medical center. Oropharyngeal (OP) and deep endotracheal (ET) secretions were sampled within 24 h of intubation and every 48-72 h thereafter. Bacterial community profiling was carried out by purifying DNA, PCR amplification of 16S ribosomal RNA (rRNA) gene sequences, deep sequencing, and bioinformatic community analysis. We compared enrolled subjects to a cohort of healthy subjects who had lower respiratory tract sampling by bronchoscopy. In contrast to the diverse upper respiratory tract and lower respiratory tract microbiota found in healthy controls, critically ill subjects had lower initial diversity at both sites. Diversity further diminished over time on the ventilator. In several subjects, the bacterial community was dominated by a single taxon over multiple time points. The clinical diagnosis of LRTI ascertained by chart review correlated with low community diversity and dominance of a single taxon. Dominant taxa matched clinical bacterial cultures where cultures were obtained and positive. In several cases, dominant taxa included bacteria not detected by culture, including Ureaplasma parvum and Enterococcus faecalis.ConclusionsLongitudinal analysis of respiratory tract microbiota in critically ill patients provides insight into the pathogenesis and diagnosis of LRTI. 16S rRNA gene sequencing of endotracheal aspirate samples holds promise for expanded pathogen identification.

Project description:Gut microbiome (GMB) disturbance can induce chronic low-grade inflammation, which is closely related to the occurrence and development of osteoarthritis (OA). However, the relationship between GMB and OA remains unclear. In this study, we collected stool samples from OA patients and healthy people, and performed Alpha diversity, Beta diversity, MetaStat, and LEfSe analysis by 16S rRNA sequencing to find out the species with significant difference between the two groups. Random forest analysis was performed to find out biomarkers that could distinguish between OA patients and healthy people. PICRUSt and Bugbase analysis were used to compare the difference in functions and phenotypes. Multivariate linear regression analysis (MaAsLin) was used to adjust for gender, age, and body mass index (BMI). The results showed that there was a significant difference in the overall composition of GMB between the two groups (p = 0.005). After adjusting for gender, age, and BMI, we found that p_Bacteroidota (Q = 0.039), c_Bacteroidia (Q = 0.039), and o_Bacteroidales (Q = 0.040) were enriched in the OA group, while s_Prevotella_copri (Q = 0.001) was enriched in the healthy control group. Prevotella could distinguish between OA patients and healthy people with a better diagnostic power (AUC = 77.5%, p < 0.001, 95% CI: 66.9-88.1%). The functions of DNA transcription, amino acid metabolism (including histidine, lysine, and isoleucine), ATP metabolism, and phospholipid metabolism significantly decreased, while glucose metabolism, protein acetylation, and aspartate kinase activity significantly increased in the OA group. In terms of phenotypes, we found that the relative abundance of aerobic (p = 0.003) and Gram-negative (p < 0.001) was higher in the OA group, while contains mobile elements (p = 0.001) and Gram-positive (p < 0.001) were higher in the healthy control group. Our study preliminarily demonstrated that there were differences in the composition, function, and phenotype of GMB in stool samples between OA patients and healthy people, which provided a novel perspective on further study in OA.

Dataset Information

The biodiversity Composition of Microbiome in Ovarian Carcinoma Patients.

Publications

The biodiversity Composition of Microbiome in Ovarian Carcinoma Patients.

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